Amazon Science Homepage

<!DOCTYPE html> <html class="HomePage" lang="en"> <head><script type="text/javascript" src="https://web-static.archive.org/_static/js/bundle-playback.js?v=7YQSqjSh" charset="utf-8"></script> <script type="text/javascript" src="https://web-static.archive.org/_static/js/wombat.js?v=txqj7nKC" charset="utf-8"></script> <script>window.RufflePlayer=window.RufflePlayer||{};window.RufflePlayer.config={"autoplay":"on","unmuteOverlay":"hidden"};</script> <script type="text/javascript" src="https://web-static.archive.org/_static/js/ruffle/ruffle.js"></script> <script type="text/javascript"> __wm.init("https://web.archive.org/web"); __wm.wombat("https://www.amazon.science/","20200722111032","https://web.archive.org/","web","https://web-static.archive.org/_static/", "1595416232"); </script> <link rel="stylesheet" type="text/css" href="https://web-static.archive.org/_static/css/banner-styles.css?v=p7PEIJWi" /> <link rel="stylesheet" type="text/css" href="https://web-static.archive.org/_static/css/iconochive.css?v=3PDvdIFv" />  <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=5"> <style data-cssvarsponyfill="true"> :root { --primaryColor: #007cb6; --secondaryColor: #e3661b; --primaryTextColor: #232f3e; --secondaryTextColor: #6c7778; --headerBgColor: #ffffff; --headerBorderColor: #aab7b8; --headerMenuBgColor: #fafafa; --headerMenuSubNavTextColor: #000000; --aboveBgColor: #fafafa; --belowBgColor: #fafafa; --footerBgColor: #232f3e; --footerTextColor: #ffffff; --buttonBgColor: transparent; --buttonTextColor: #007cb6; --primaryHeadlineFont: Amazon Ember; --secondaryHeadlineFont: Amazon Ember; --bodyFont: Amazon Ember; --contentWidth: 1240px; } </style> <link data-cssvarsponyfill="true" class="Webpack-css" rel="stylesheet" href="https://web.archive.org/web/20200722111032cs_/https://assets.amazon.science/resource/0000016e-128c-d913-a16f-9edc0a5f0000/styleguide/All.min.1e622440f59db7bdc6e637104c536e0c.css"> <title>Amazon Science Homepage</title><meta name="description" content="Learn about Amazon's approach to customer-obsessed science. 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of products and services at the lowest prices.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/knowledge-management-and-data-quality" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-title">Information and knowledge management</div> <div class="PromoD-description">Structuring the world’s information as it relates to everything available on Amazon.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-title">Machine learning</div> <div class="PromoD-description">Developing algorithms and statistical models that computer systems use to perform tasks without explicit instructions, relying on patterns and inference instead.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/operations-research-and-optimization" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-title">Operations research and optimization</div> <div class="PromoD-description">Streamlining operations to deliver orders to you faster, more conveniently, and more economically.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/robotics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-title">Robotics</div> <div class="PromoD-description">Delivering a faster and more consistent customer experience through a variety of robotic technologies.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/search-and-information-retrieval" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-title">Search and information retrieval</div> <div class="PromoD-description">Developing advanced techniques to analyze behavioral patterns, lexical matches, and semantic matches to surface the most relevant recommendations in response to your queries.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/security-privacy-and-abuse-prevention" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Security.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/35/42/bdaf2a4c4e8d887ffcfdaf03ddee/security.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Security.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/35/42/bdaf2a4c4e8d887ffcfdaf03ddee/security.svg"> </div> <div class="PromoD-title">Security, privacy, and abuse prevention</div> <div class="PromoD-description">Creating a secure suite of hardware, software, and services with privacy, while giving you control over your information.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/sustainability" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> <div class="PromoD-title">Sustainability</div> <div class="PromoD-description">Taking a broad, science-based approach to reach net zero carbon by 2040.</div> </div> </a> </div> </li> </ul> </div> </section> </div> </div> </div> </li> <li class="Navigation-items-item"><div class="NavigationItem"> <div class="NavigationItem-text"> <a class="NavigationItem-text-link" 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data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/cloud-and-systems" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-title">Cloud and systems</div> <div class="PromoD-description">Developing new technologies that offer increased computing power, expanded database storage, faster content delivery, and other capabilities.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/computer-vision" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-title">Computer vision</div> <div class="PromoD-description">Helping devices see and understand our visual world.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-title">Conversational AI / Natural-language processing</div> <div class="PromoD-description">Building software and systems that help people communicate with computers naturally, as if communicating with family and friends.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/economics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Economics.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/a9/bc/ab88878c4faebca412cbef3b022b/economics.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Economics.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/a9/bc/ab88878c4faebca412cbef3b022b/economics.svg"> </div> <div class="PromoD-title">Economics</div> <div class="PromoD-description">Developing sophisticated approaches and systems to deliver the broadest selection of products and services at the lowest prices.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/knowledge-management-and-data-quality" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-title">Information and knowledge management</div> <div class="PromoD-description">Structuring the world’s information as it relates to everything available on Amazon.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-title">Machine learning</div> <div class="PromoD-description">Developing algorithms and statistical models that computer systems use to perform tasks without explicit instructions, relying on patterns and inference instead.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/operations-research-and-optimization" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-title">Operations research and optimization</div> <div class="PromoD-description">Streamlining operations to deliver orders to you faster, more conveniently, and more economically.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/robotics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-title">Robotics</div> <div class="PromoD-description">Delivering a faster and more consistent customer experience through a variety of robotic technologies.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/search-and-information-retrieval" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-title">Search and information 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data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/62ab477/2147483647/strip/true/crop/1806x1013+106+287/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F9d%2F4b%2F0051a7e747d2935f73dbfa4667fe%2Faccuracy-fairness-trade-off.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/amazon-researchers-win-best-paper-award-for-helping-promote-fairness-in-ai" data-cms-ai="0">Amazon researchers win best-paper award for promoting fairness in AI</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 20, 2020</div> </div> <div class="PromoA-description">Method presented to ICML workshop works with any machine learning model and fairness criterion.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="article" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="“You’re trying to predict the unpredictable”" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/latest-news/amazon-economist-test-of-time-award-acm-conference-economics-computation" data-cms-ai="0"> <img class="Image" alt="Dean Foster, an economist who works on optimizing Amazon's supply chain technologies, is seen holding an Amazon package he ordered from the middle of a forest in Japan." width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/0d771db/2147483647/strip/true/crop/3019x1693+2+905/resize/535x300!/brightness/2x-5/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2Fd5%2Fbd%2F096211974b22a0a4340e91fb25e9%2Fdean-foster-package.jpg"> </a> <div class="PromoA-media-credit">Courtesy Dean Foster</div> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/latest-news/amazon-economist-test-of-time-award-acm-conference-economics-computation" data-cms-ai="0">“You’re trying to predict the unpredictable”</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 16, 2020</div> </div> <div class="PromoA-description">Amazon scientist Dean Foster and coauthor receive “test of time” award for paper authored 23 years ago.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/economics" data-cms-ai="0">Economics</a> </div> </div> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="blogPost" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="When does transfer learning work?" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/when-does-transfer-learning-work" data-cms-ai="0"> <img class="Image" alt="Conditional probability.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/b0d7c80/2147483647/strip/true/crop/2000x1121+0+4/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F68%2F6b%2F8ec10fde4d4a8a67b0e8768df56b%2Fconditional-probability.png"> </a> <div 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</div> <div class="PromoB-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/knowledge-management-and-data-quality" data-cms-ai="0">Information and knowledge management</a> </div> </div> <div class="PromoB-aside"> <div class="PromoB-calendarTime"><span class="ParsedDate-item">July 25 - 30, 2020</span> </div> </div> </div> </li> <li class="ListG-items-item"> <div class="PromoB" data-content-type="event"> <div class="PromoB-content"> <div class="PromoB-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conferences-and-events/jsm-2020" data-cms-ai="0">JSM 2020</a> </div> <div class="PromoB-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> <div class="PromoB-aside"> <div class="PromoB-calendarTime"><span class="ParsedDate-item">August 1 - 6, 2020</span> </div> </div> </div> </li> </ul> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="blogPost" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="ICML: “Test of time” paper shows how times have changed" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/icml-test-of-time-paper-shows-how-times-have-changed" data-cms-ai="0"> <img class="Image" alt="Temperature samples.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/0d83438/2147483647/strip/true/crop/923x517+2+81/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2Ff5%2F7e%2F4f57fefa4befb6847a6b75b506fb%2Ftemperature-samples.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/icml-test-of-time-paper-shows-how-times-have-changed" data-cms-ai="0">ICML: “Test of time” paper shows how times have changed</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 09, 2020</div> </div> <div class="PromoA-description">Amazon scientist’s award-winning paper predates — but later found applications in — the deep-learning revolution.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="blogPost" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Using unlabeled data to improve sequence labeling" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/using-unlabeled-data-to-improve-sequence-labeling" data-cms-ai="0"> <img class="Image" alt="SeqVAT architecture.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/8524593/2147483647/strip/true/crop/1181x662+41+94/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F3f%2F1d%2Fdd0ff7214092ae1c5acc0d319948%2Fseqvat-architecture.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/using-unlabeled-data-to-improve-sequence-labeling" data-cms-ai="0">Using unlabeled data to improve sequence labeling</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 08, 2020</div> </div> <div class="PromoA-description">New method extends virtual adversarial training to sequence-labeling tasks, which assign different labels to different words of an input sentence.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0">Conversational AI / Natural-language processing</a> </div> </div> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="article" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Amazon scientist Matthias Seeger receives ICML "test of time" award" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/latest-news/amazon-scientist-matthias-seeger-receives-icml-test-of-time-award" data-cms-ai="0"> <img class="Image" alt="Matthias Seeger " width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/3a7fa21/2147483647/strip/true/crop/456x256+0+68/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F02%2F68%2F8fd83def439c971c6b576fd690b3%2Fmatthias-seeger-amazon.jpg"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/latest-news/amazon-scientist-matthias-seeger-receives-icml-test-of-time-award" data-cms-ai="0">Amazon scientist Matthias Seeger receives ICML "test of time" award</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 02, 2020</div> </div> <div class="PromoA-description">Seeger and three coauthors are honored for paper that forged durable links between previously separate domains.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> <li class="ListA-items-item"> <div class="PromoA" data-content-type="blogPost" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Adversarial training improves product discovery" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/adversarial-training-improves-product-discovery" data-cms-ai="0"> <img class="Image" alt="Hard examples.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/aec12f8/2147483647/strip/true/crop/1250x701+0+2/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2Fa4%2Ff6%2F9088038248abbe3d57baf407fa2d%2Fhard-examples.png"> </a> <div class="PromoA-media-credit">Credit: Stacy Reilly</div> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/adversarial-training-improves-product-discovery" data-cms-ai="0">Adversarial training improves product discovery</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 02, 2020</div> </div> <div class="PromoA-description">Method automatically generates negative training examples for deep-learning model.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/search-and-information-retrieval" data-cms-ai="0">Search and information retrieval</a> </div> </div> </div> </li> </ul> </div><ps-list-loadmore class="ListE" data-hexagon-collage="list-e"> <div class="ListE-header-wrapper"> <h2 class="ListE-header">Recent publications</h2><a class="ListE-header-button" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications" data-cms-ai="0">View All</a> </div> <div class="ListE-body"> <ul class="ListE-items" data-list-loadmore-items> <li class="ListE-items-item"> <div class="PromoF" data-content-type="publication" data-no-media> <div class="PromoF-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications/a-linear-bandit-for-seasonal-environments" data-cms-ai="0">A linear bandit for seasonal environments</a> </div> <div class="PromoF-details"> <div class="PromoF-authors"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/giuseppe-di-benedetto" data-cms-ai="0">Giuseppe Di Benedetto</a>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/vito-bellini" data-cms-ai="0">Vito Bellini</a>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/giovanni-zappella" data-cms-ai="0">Giovanni Zappella</a> </div> <div class="PromoF-journal"> <span class="Link">ICML 2020 Workshop on Human-in-the-Loop Learning (HILL) 2020</span> </div> <div class="PromoF-date">2020</div> </div> <div class="PromoF-content"> <div class="PromoF-body"> <ps-truncatable data-truncation-line-count="3" data-truncation-link-label="Read More" class="PromoF-description">Contextual bandit algorithms are extremely popular and widely used in recommendation systems to provide online personalized recommendations. A recurrent assumption is the stationarity of the reward function, which is rather unrealistic in most of the real-world applications. In the music recommendation scenario for instance, people’s music taste can abruptly change during certain events, such as Halloween</ps-truncatable> <div class="PromoF-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </div> </li> <li class="ListE-items-item"> <div class="PromoF" data-content-type="publication" data-no-media> <div class="PromoF-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications/motion-excited-sampler-video-adversarial-attack-with-sparked-prior" data-cms-ai="0">Motion-excited sampler: Video adversarial attack with sparked prior</a> </div> <div class="PromoF-details"> <div class="PromoF-authors"> <span class="Link">Hu Zhang</span>, <span class="Link">Linchao Zhu</span>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/yi-zhu" data-cms-ai="0">Yi Zhu</a>, <span class="Link">Yi Yang</span> </div> <div class="PromoF-journal"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conferences-and-events/eccv-2020" data-cms-ai="0">ECCV 2020</a> </div> <div class="PromoF-date">2020</div> </div> <div class="PromoF-content"> <div class="PromoF-body"> <ps-truncatable data-truncation-line-count="3" data-truncation-link-label="Read More" class="PromoF-description">Deep neural networks are known to be susceptible to adversarial noise, which is tiny and imperceptible perturbation. Most previous works on adversarial attack mainly focus on image models, while the vulnerability of video models is less explored. In this paper, we aim to attack video models by utilizing intrinsic movement patterns and regional relative motion among video frames. We propose an effective</ps-truncatable> <div class="PromoF-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/computer-vision" data-cms-ai="0">Computer vision</a> </div> </div> </div> </div> </li> <li class="ListE-items-item"> <div class="PromoF" data-content-type="publication" data-no-media> <div class="PromoF-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications/optimal-continual-learning-has-perfect-memory-and-is-np-hard" data-cms-ai="0">Optimal continual learning has perfect memory and is NP-HARD</a> </div> <div class="PromoF-details"> <div class="PromoF-authors"> <span class="Link">Jeremias Knoblauch</span>, <span class="Link">Hisham Husain</span>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/tom-diethe" data-cms-ai="0">Tom Diethe</a> </div> <div class="PromoF-journal"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conferences-and-events/icml-2020" data-cms-ai="0">ICML 2020</a> </div> <div class="PromoF-date">2020</div> </div> <div class="PromoF-content"> <div class="PromoF-body"> <ps-truncatable data-truncation-line-count="3" data-truncation-link-label="Read More" class="PromoF-description">Continual Learning (CL) algorithms incrementally learn a predictor or representation across multiple sequentially observed tasks. Designing CL algorithms that perform reliably and avoid so-called catastrophic forgetting has proven a persistent challenge. The current paper develops a theoretical approach that explains why. In particular, we derive the computational properties which CL algorithms would have</ps-truncatable> <div class="PromoF-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </div> </li> <li class="ListE-items-item"> <div class="PromoF" data-content-type="publication" data-no-media> <div class="PromoF-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications/linear-bandits-with-stochastic-delayed-feedback" data-cms-ai="0">Linear bandits with stochastic delayed feedback</a> </div> <div class="PromoF-details"> <div class="PromoF-authors"> <span class="Link">Claire Vernade</span>, <span class="Link">Alexandra Carpentier</span>, <span class="Link">Tor Lattimore</span>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/giovanni-zappella" data-cms-ai="0">Giovanni Zappella</a>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/beyza-ermis" data-cms-ai="0">Beyza Ermis</a>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/michael-brueckner" data-cms-ai="0">Michael Brueckner</a> </div> <div class="PromoF-journal"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conferences-and-events/icml-2020" data-cms-ai="0">ICML 2020</a> </div> <div class="PromoF-date">2020</div> </div> <div class="PromoF-content"> <div class="PromoF-body"> <ps-truncatable data-truncation-line-count="3" data-truncation-link-label="Read More" class="PromoF-description">Stochastic linear bandits are a natural and well-studied model for structured exploration/exploitation problems and are widely used in applications such as online marketing and recommendation. One of the main challenges faced by practitioners hoping to apply existing algorithms is that usually the feedback is randomly delayed and delays are only partially observable. For example, while a purchase is usually</ps-truncatable> <div class="PromoF-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </div> </li> <li class="ListE-items-item"> <div class="PromoF" data-content-type="publication" data-no-media> <div class="PromoF-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/publications/efficient-intervention-design-for-causal-discovery-with-latents" data-cms-ai="0">Efficient intervention design for causal discovery with latents</a> </div> <div class="PromoF-details"> <div class="PromoF-authors"> <span class="Link">Raghavendra Addanki</span>, <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/author/shiva-kasiviswanathan" data-cms-ai="0">Shiva Prasad Kasiviswanathan</a>, <span class="Link">Andrew McGregor</span>, <span class="Link">Cameron Musco </span> </div> <div class="PromoF-journal"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conferences-and-events/icml-2020" data-cms-ai="0">ICML 2020</a> </div> <div class="PromoF-date">2020</div> </div> <div class="PromoF-content"> <div class="PromoF-body"> <ps-truncatable data-truncation-line-count="3" data-truncation-link-label="Read More" class="PromoF-description">We consider recovering a causal graph in presence of latent variables, where we seek to minimize the cost of interventions used in the recovery process. We consider two intervention cost models: (1) a linear cost model where the cost of an intervention on a subset of variables has a linear form, and (2) an identity cost model where the cost of an intervention is the same, regardless of what variables it</ps-truncatable> <div class="PromoF-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </div> </li> </ul> <div class="ListE-nextPage" data-list-loadmore-pagination> <a class="Link" href="?0000016e-8f90-d381-abee-cfb5f49d0000-page=2" data-cms-ai="0">Load More</a> </div> </div> </ps-list-loadmore><div class="ListD"> <div class="ListD-header-wrapper"> <h2 class="ListD-header">Research areas</h2> </div> <ul class="ListD-items"> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/cloud-and-systems" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-title">Cloud and systems</div> <div class="PromoD-description">Developing new technologies that offer increased computing power, expanded database storage, faster content delivery, and other capabilities.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/computer-vision" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-title">Computer vision</div> <div class="PromoD-description">Helping devices see and understand our visual world.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-title">Conversational AI / Natural-language processing</div> <div class="PromoD-description">Building software and systems that help people communicate with computers naturally, as if communicating with family and friends.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/economics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Economics.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/a9/bc/ab88878c4faebca412cbef3b022b/economics.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Economics.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/a9/bc/ab88878c4faebca412cbef3b022b/economics.svg"> </div> <div class="PromoD-title">Economics</div> <div class="PromoD-description">Developing sophisticated approaches and systems to deliver the broadest selection of products and services at the lowest prices.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/knowledge-management-and-data-quality" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-title">Information and knowledge management</div> <div class="PromoD-description">Structuring the world’s information as it relates to everything available on Amazon.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-title">Machine learning</div> <div class="PromoD-description">Developing algorithms and statistical models that computer systems use to perform tasks without explicit instructions, relying on patterns and inference instead.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/operations-research-and-optimization" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-title">Operations research and optimization</div> <div class="PromoD-description">Streamlining operations to deliver orders to you faster, more conveniently, and more economically.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/robotics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-title">Robotics</div> <div class="PromoD-description">Delivering a faster and more consistent customer experience through a variety of robotic technologies.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/search-and-information-retrieval" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-title">Search and information retrieval</div> <div class="PromoD-description">Developing advanced techniques to analyze behavioral patterns, lexical matches, and semantic matches to surface the most relevant recommendations in response to your queries.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/security-privacy-and-abuse-prevention" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Security.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/35/42/bdaf2a4c4e8d887ffcfdaf03ddee/security.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Security.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/35/42/bdaf2a4c4e8d887ffcfdaf03ddee/security.svg"> </div> <div class="PromoD-title">Security, privacy, and abuse prevention</div> <div class="PromoD-description">Creating a secure suite of hardware, software, and services with privacy, while giving you control over your information.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/sustainability" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> <div class="PromoD-title">Sustainability</div> <div class="PromoD-description">Taking a broad, science-based approach to reach net zero carbon by 2040.</div> </div> </a> </div> </li> </ul> </div><div class="ListN"> <div class="ListN-header-wrapper"> <h2 class="ListN-header">Working at Amazon</h2><a class="ListN-header-button" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/working-at-amazon" data-cms-ai="0">Learn More</a> </div> <ul class="ListN-items"> <li class="ListN-items-item"> <div class="PromoC" data-content-type="article" data-image-align="left"> <div class="PromoC-media" data-hexagon-collage="large-promo-image-left"> <a class="Link" aria-label="Amazon Scholar Kathleen McKeown takes stock of natural language processing; where we are, and where we’re going" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/working-at-amazon/amazon-scholar-kathleen-mckeown-takes-stock-of-natural-language-processing-where-we-are-and-where-were-going" data-cms-ai="0"> <img class="Image" alt="Kathleen McKeown " width="1200" height="680" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/6f61c14/2147483647/strip/true/crop/2483x1407+19+0/resize/1200x680!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5b%2F1d%2F816b6633455e9d438ca6e604cb2c%2Fkathleen-mckeown1.jpg"> </a> <div class="PromoC-media-credit">Credit: Columbia University </div> </div> <div class="PromoC-content"> <div class="PromoC-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/working-at-amazon/amazon-scholar-kathleen-mckeown-takes-stock-of-natural-language-processing-where-we-are-and-where-were-going" data-cms-ai="0">Amazon Scholar Kathleen McKeown takes stock of natural language processing; where we are, and where we’re going</a> </div> <div class="PromoC-details"> <div class="PromoC-date">July 06, 2020</div> </div> <div class="PromoC-description">After nearly 40 years of research, this year’s ACL 2020 keynote speaker sees big improvements coming in three key areas.</div> <div class="PromoC-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0">Conversational AI / Natural-language processing</a> </div> <div class="PromoC-cta"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/working-at-amazon/amazon-scholar-kathleen-mckeown-takes-stock-of-natural-language-processing-where-we-are-and-where-were-going" data-cms-ai="0">Read More</a> </div> </div> </div> </li> </ul> </div><ps-carousel class="ListI"> <div class="ListI-header-wrapper"> <h2 class="ListI-header">Work with us</h2><a class="ListI-header-button" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/careers" data-cms-ai="0">See More Jobs</a> </div> <div class="ListI-mask"> <div class="ListI-slides"> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1213635/applied-scientist-ii?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Applied Scientist II</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, MA, Cambridge</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Alexa is the groundbreaking voice service that powers Echo and other devices designed around your voice. Our team is creating the science and technology behind Alexa. We’re working hard, having fun, and making history. Come join our team! You will have an enormous opportunity to impact the customer experience, design, architecture, and implementation of a cutting edge product used every day by people you know.We’re looking for a passionate, talented, and inventive scientist to help build industry-leading conversational technologies that customers love. Our team's mission is the enable Alexa to understand sounds and vocalization beyond speech. As an Applied Scientist, you will work with talented peers to develop novel machine learning algorithms and modeling techniques to advance the state of the art in speech and audio processing. Your work will directly impact our customers in the form of novel products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. You will mentor junior scientists, create and drive new initiatives.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1213593/applied-scientist-alexa-speech?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Applied Scientist, Alexa Speech</a> </div> <div class="PromoA-details"> <div class="PromoA-location">CA, ON, Toronto</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.As a Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management.Position Responsibilities: · Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. · Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. · Routinely build and deploy ML models on available data. · Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1213563/sr-applied-scientist-prime-video?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0"> Sr. Applied Scientist, Prime Video</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon Prime Video is changing the way people watch movies, TV shows, Channels and Live Events, offering the greatest choice in what to watch on-demand or in real-time on large gamut of devices (mobile phone, PCs, Macs, gaming consoles and Fire TV etc.). We are at the forefront of the entertainment industry and growing fast - now available in more than 240 countries and territories worldwide. We work in a dynamic, and exciting environment where innovating on behalf of our customers is at the heart of everything we do.Digital Media Engineering (DME) builds and operates systems that ingest, process and transform digital media (e.g. video, audio, timed text) into engaging experience for streamers. We leverage Machine Learning (ML) and Computer Vision (CV) tech to remove defects from the media, semantically analyze (e.g. video meta-data extraction) and enrich (e.g. annotations) it to shape the streamer CX before (Search, Discovery & Detail Page) and after (Skip Intro, Next Up) the “play button is pressed”.We are building a new team for Applied Science and are looking for specialized talent to join us in our mission to build deep expertise in 1) Semantic video understanding – for unlocking information from catalog to enhance search and discovery experiences; 2) Automatic extraction and generation of content – for new and engaging experiences and increasing coverage by auto generating Subs and Dubs; and 3) Multimodal learning – for identifying the scene boundaries for broad application in various video streaming solutions like insertion of advertisements at accurate scene transitions.As an Applied Scientist you will be the founding member of this team and will push the state of art in the computer vision and its application to video centric digital media. You will be responsible for new experimental solutions that combine the latest findings in cutting-edge computer vision and machine learning to build compelling demos and illustrative results. You will work with a team of engineers and scientists who are passionate about using machine learning to analyze terabytes of data, build automated systems and solve problems that matter to our customers.It has never been a more exciting time for AI and Computer Vision.We are in a green-field space of research which is overdue for disruption. To know more about this once-in-a-lifetime opportunity to shape the future of streaming video - please mail/chime me at – vimalb AT amazon DOT com.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1211936/senior-applied-scientist-sponsored-display-advertising?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Senior Applied Scientist - Sponsored Display Advertising</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon is investing in building a world class advertising business and we are responsible for defining and delivering a self-service display advertising product that drive discovery and sales across multi channels (onsite, offsite, mobile, desktop). Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class product. We are highly motivated, collaborative and team. We are growing at an unprecedented rate with a seemingly endless range of new opportunities.In Sponsored Display Advertising team, our charter is to enable all advertisers (vendors, seller brand owners, authors, traders, agencies and software solution providers) to grow their brand and business with and on Amazon via multi-channel advertising at scale. We are looking for building a nimble science team who are passionate about applying advanced ML and statistical techniques to solve real-world, ambiguous and complex challenges to optimize and improve the product performance. As a scientist on the team, you can be involved in every aspect of the process - from idea generation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. The systems that you help to build will operate at massive scale to display ads to customers around the world. From day one, you will be working with experienced scientists, engineers, and designers who love what they do.We are looking for Senior Applied Scientist who can help us take our products to the next level who has deep passion for building machine-learning solutions; ability to communicate data insights and scientific vision, and has a proven track record of execute complex projects.As an Senior Applied Scientist in Sponsored Display, you will:· Conduct hands-on data analysis, build large-scale machine-learning models and pipelines· Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production· Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management· Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving· Provide technical leadership, research new machine learning approaches to drive continued scientific innovation· Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences· Help attract and recruit technical talent</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1210185/research-scientist-amz4112?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Research Scientist - AMZ4112</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">MULTIPLE POSITIONS AVAILABLEEntity: Amazon.com Services LLC, an Amazon.com CompanyTitle: Research ScientistLocation: Seattle, WAPosition Responsibilities:Interact with various software and business groups to develop an understanding of their business requirements and operational processes. Utilize acquired knowledge and business judgment to build decision-supporting and operational tools to improve the bottom line. Build quantitative mathematical models to represent a wide range of supply chain, transportation and logistics systems. implement these models and tools through the use of modeling languages and engineering code in software languages such as Java, C++, C# or C. Gather required data for analysis and mathematical model building by writing ad-hoc scripts and database queries. Perform quantitative, economic, and numerical performance analyses of these systems under uncertainty using statistical and optimization tools. Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements to realize improvements. Design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. Create software prototypes to verify and validate the devised solutions methodologies. Integrate prototypes into production systems using standard software development tools and methodologies.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1208801/applied-scientist-ii-for-adsecon?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Applied Scientist II for AdsEcon</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Work at the intersection of data science and economics.The DAC AdsEcon Team is looking for a Data Scientist III to help and be part of a team to put cutting edge economic and data science advertising research into production. We are looking for a unique individual who is interested in bigger picture strategic thinking but with the passion for big data.Advertising is used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to the high level leaders.If you have a background in economics, computer science, statistics, or mathematics and have a passion for solving large, and impactful problems, this is the job for you. Key responsibilities of Applied Scientist include the following:· Partnering with economists and senior team members to drive science improvements and implement technical solutions at the cutting edge of machine learning and econometrics· · Design, implement, test, deploy, and maintain large-scale Econ/ML models.· · Build interpretable statistical models and analyze experiment results to answer questions that will drive high impact decisions across Amazon.About Amazon's Advertising business:Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1209441/applied-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0"> Applied Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, CA, Sunnyvale</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon is looking for a passionate, talented, and inventive Senior Scientist to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of novel products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. You will mentor junior scientists, create and drive new initiatives.We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1208025/data-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, MD, Baltimore</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Are you passionate about networking, Big Data, machine learning and cybersecurity? Are you ready for an exciting opportunity to work with some of the best data scientists and technologies and thrive in a super dynamic environment? Do you want to help secure millions of enterprises and organizations who are running their business in cloud at an unprecedented scale?How about making a difference in making the whole Internet more secure?Amazon Web Services (AWS) is looking for data scientists to joint its cyber-security analytics team.You will leverage cutting-edge data technologies to perform statistical inference, classification, clustering, and various predictive analysis for a wide spectrum of problems in cybersecurity. As a key member of the technical team, you will translate cyber and network security related requirements into sophisticated models to help extract new insights and drive new initiatives to defend against cyber-attacks. You will be working with a large variety and huge volume of of data sets, advanced security and data technologies, and world-class operation teams to create awesome analyses for cyber security.The preferred location for this position is Baltimore, MD, but it can also be located in Herndon, VA or Arlington, VA (HQ2).</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1208005/data-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, MD, Baltimore</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Are you passionate about networking, Big Data, machine learning and cybersecurity? Are you ready for an exciting opportunity to work with some of the best data scientists and technologies and thrive in a super dynamic environment? Do you want to help secure millions of enterprises and organizations who are running their business in cloud at an unprecedented scale?How about making a difference in making the whole Internet more secure?Amazon Web Services (AWS) is looking for data scientists to joint its cyber-security analytics team.You will leverage cutting-edge data technologies to perform statistical inference, classification, clustering, and various predictive analysis for a wide spectrum of problems in cybersecurity. As a key member of the technical team, you will translate cyber and network security related requirements into sophisticated models to help extract new insights and drive new initiatives to defend against cyber-attacks. You will be working with a large variety and huge volume of of data sets, advanced security and data technologies, and world-class operation teams to create awesome analyses for cyber security.The preferred location for this position is Baltimore, MD, but it can also be located in Herndon, VA or Arlington, VA (HQ2).</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1207996/data-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, MD, Baltimore</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Are you passionate about networking, Big Data, machine learning and cybersecurity? Are you ready for an exciting opportunity to work with some of the best data scientists and technologies and thrive in a super dynamic environment? Do you want to help secure millions of enterprises and organizations who are running their business in cloud at an unprecedented scale?How about making a difference in making the whole Internet more secure?Amazon Web Services (AWS) is looking for data scientists to joint its cyber-security analytics team.You will leverage cutting-edge data technologies to perform statistical inference, classification, clustering, and various predictive analysis for a wide spectrum of problems in cybersecurity. As a key member of the technical team, you will translate cyber and network security related requirements into sophisticated models to help extract new insights and drive new initiatives to defend against cyber-attacks. You will be working with a large variety and huge volume of of data sets, advanced security and data technologies, and world-class operation teams to create awesome analyses for cyber security.The preferred location for this position is Baltimore, MD, but it can also be located in Herndon, VA or Arlington, VA (HQ2).</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1207542/sr-data-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Sr. Data Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, CO, Denver</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. As an ML Solutions Lab data scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.We’re looking for talented data scientists capable of applying classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.The primary responsibilities of this role are to:· Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries· Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them· Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithmsThis position requires travel of up to 25%.This position requires that the candidate selected be a U.S. citizen and must currently possess an active Top Secret security clearance. The position further requires that, after start, the selected candidate obtain and maintain an active TS/SCI security clearance with polygraph and satisfy other security related requirements.**If interested in more details please reach out to Chris Widmann (widmannc@amazon.com)**</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1207396/data-scientist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Hundreds of millions of customers, billions of transactions, petabytes of data… How to use the world’s richest collection of e-commerce data to provide superior value and better paying experience to customers? The Amazon Payments Team manages all Amazon branded payment offerings globally. These offerings are growing rapidly and we are continuously adding new market-leading features and launching new products. Amazon.com has a culture of data-driven decision-making and demands business intelligence that is timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities.Our team of high caliber software developers, data scientists, statisticians, business analysts and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between click through rate, approval rates and lifetime value. In order to accomplish this we leverage the wealth of Amazon’s information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon’s technological infrastructure to display the right offerings in real time.We are seeking a strong, business savvy Data Scientist to tackle the growing complexity of our international business by developing models, data-driven insights, and frameworks to better serve our customers around the world.Responsibilities include:· Model development· · Testing multiple hypothesis· · Identify opportunities and key criteria to drive analytical reporting.· · Conducting deep dive analyses of business problems and formulate conclusions and recommendations to be presented to senior leadership.· · Producing written recommendations and insights for key stakeholders that will help shape effective metric development and reporting.· · Simplifying and automating reporting, audits, and other data-driven activities; build solutions to have maximum scale and self-service ability by stakeholders.· · Recognizing and adopting best practices in reporting and analysis: data integrity, analysis, and documentation.· · Supporting business with time-critical tactical data analyses.· · Understanding a broad range of Amazon’s data resources and know how, when, and which to use and which not to use.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1207299/economist?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Economist</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon cross-channel marketing measurement and optimization team is looking for an economist to join us. The candidate will contribute to the science of marketing attribution systems and work with partner teams to design and analyze experiments.This role requires an individual with strong quantitative modeling skills and the ability to apply statistical/machine learning, econometric, and experimental design methods.The candidate should have strong communication skills to work closely with stakeholders to translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.Overall, the candidate’s responsibilities include:· Build econometric models and conduct statistical/machine learning analyses to measure the financial impact of cross channel marketing spend· Design and measure experiments· Build scalable analytic solutions using state of the art tools based on large datasets</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1206926/manager-research-science?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Manager, Research Science</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, MA, Cambridge</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Interested in Amazon Alexa? We’re building the speech and language solutions behind Amazon Alexa and Amazon products and services such as the Amazon Echo and Dot. Come join us!We're looking for a Research Science Manager who combines exceptional technical, research and analytical capabilities to build and lead a team that will be integral to the continued improvement of Amazon Alexa. As a Research Manager, you will be responsible for leading a team of researchers and data experts in the design, development, testing, and deployment of speech and language data processes and model improvements, supporting a range of products.This involves:· Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential.· · Providing technical and scientific guidance to your team members.· · Communicating effectively with senior management as well as with colleagues from science, engineering and business backgrounds.· · Supporting the career development of your team members.A successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, demonstrated experience in people management, excellent project management skills, great communication skills, and the motivation to achieve results in a fast-paced environment.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1206398/data-scientist-ii?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist II</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon Business – Amazon’s B2B Purchasing Platform - is redefining the way businesses buy. Growing at a staggering pace, Amazon Business has become a $10 billion dollar business within just 5 years of launch! We at Amazon Business are applying the same entrepreneurial and innovative approach that has made Amazon successful in the ecommerce and software services industry to create an unparalleled shopping experience for business purchasing. We build solutions to enable B2B customers to discover, research, and buy products and services relevant for them. Our customers include individual professionals, small businesses to large institutions (and everything in between) from different industry verticals - across seven countries!To support this vision, we are looking for a Data Scientist supporting Amazon Business (AB) Sales and Marketing business units. As a Data Scientist, you will leverage advanced analytical and machine learning techniques to evolve the way we prioritize customer leads for Sales outreach, improve Sales data quality through experiments including leveraging 3rd party sources, and build hands of the wheel solutions to automatically classify and segment AB customers in suitable categories. As a Data Scientist, you will bring along outstanding analytical abilities and will be comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. Some of your key responsibilities include:· Make recommendations for new metrics, techniques, and strategies to improve methods to prioritize accounts for Sales outreach· Develop machine learning driven algorithms that establish customer personas and deliver tailored suggestions based on customer's purchase behavior and AB journey· Help Sales and Marketing uncover hidden business opportunities leveraging hard data and advanced analytical techniques· Work with cross-functional teams including Sales, Marketing, and Product to understand business requirements and build analytical solutions to achieve key business goals· Collaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality· Foster culture of continuous engineering improvement through mentoring, feedback, and metrics</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1205905/applied-scientist-fixed-marketing-measurement-customer-behavior-analytics-team?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Applied Scientist - Fixed Marketing Measurement - Customer Behavior Analytics Team</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon's Marketing Science team (a part of Customer Behavior Analytics) is looking for an applied scientist with strong technical skills in causal inference to drive methodology improvements for fixed marketing measurement (TV, Digital) using customer-level data.The successful candidate will be a daring hands-on self-starter, comfortable with ambiguity, humble to seek feedback and learn from peers (scientists, economists, marketing practitioners), bold to think big, has solid attention to detail and believes in challenging themselves to raise the bar continuously. The scientist will develop production models using customer-level panel data on advertising exposure to identify the causal impact of Amazon marketing. They will work closely with media and portfolio teams to understand business needs and with a sister engineering team to productionalize solutions. The ML models will improve the efficiency of billions of dollars of marketing spend.This role requires an individual with strong quantitative modeling skills and the ability to apply statistical/machine learning, econometric, and good coding skills.The candidate should have strong communication skills to work closely with stakeholders to translate business needs into methodology and data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and ability to work in a fast-paced and ever-changing environment.Overall, the candidate’s responsibilities include:· Design and build scalable analytic solutions using ML models to measure the financial impact of cross channel marketing spend· Work with the data acquisition team on data requirements· Ensuring that state of the art statistical methods and machine learning technology are deployed to measure effectiveness of video advertising on social media· Work closely with both business units and engineering teams to formulate measurement problems and associated technical solution strategies· Develop a library of measurement, decision making and machine learning algorithms to enable data-driven decision making· Support engineering teams to build tools and applications on our unique big data platform to efficiently generate and deploy insights into decision-making systems at Amazon· Raise the bar on applications of machine learning for advertising measurement and optimization</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1205758/principal-applied-scientist-amazon-music?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Principal Applied Scientist, Amazon Music</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, CA, San Francisco</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">We are seeking a Principal Applied Scientist to break new ground in the world of understanding and classifying different forms of music, and create interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval.You'll work in a collaborative environment where you can pursue ambitious, long-term research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy their algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish research. You'll see the work of your team directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1205744/applied-scientist-consumer-cloud-security?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Applied Scientist - Consumer Cloud Security</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, CA, San Diego</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">The Consumer Cloud Security (C2S) group is responsible for the protection of customer and corporate data. We are connected to all parts of Amazon's business and it’s massive, worldwide service-oriented architecture. We are starting the work on a new mission critical system that will preserve and improve the trusted experience that Amazon provides to its customers. This is a greenfield initiative with plenty of opportunity for innovation in the security space through new machine learning techniques.We are seeking a talented, self-directed Applied Scientist to work on the cutting edge security technologies. You'll design and run experiments, research new algorithms, and find new ways of protecting Amazon's customer trust. Besides theoretical analysis and innovation, you will work closely with talented engineers to put your algorithms and models into practice. You should thrive in ambiguous environments that require to find solutions to problems that have not been solved before. You enjoy and succeed in fast paced environments where learning new concepts quickly is a must. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience in building large-scale distributed systems. Your strong communication skills enable you to work effectively with both business and technical partners.Key responsibilities:· Process and analyze large data sets using as many techniques as necessary· Deliver scalable models that can analyze large data sets efficiently· Build mathematical models to detect and classify specific data elements with high accuracy· Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.· Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1205672/data-scientist-alexa-shopping-nlu?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist, Alexa Shopping NLU</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday lifeWe are seeking a Data Scientist to be part of the NLU science team for Alexa Shopping. This is a strategic role to shape and deliver our technical strategy in developing and deploying NLU, Machine Learning solutions to our hardest customer facing problems. Our goal is to delight customers by providing a conversational interaction. These initiatives are at the heart of the organization and recognized as the innovations that will allow us to build a differentiated product that exceeds customer expectations. We're a high energy, fast growth business excited to have the opportunity to shape Alexa Shopping NLU is defined for years to come. If this role seems like a good fit, please reach out, we'd love to talk to you.This role requires working closely with business, engineering and other scientists within Alexa Shopping and across Amazon to deliver ground breaking features. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will work with a team of Language Engineers and Scientists to launch new customer facing features and improve the current features.</ps-truncatable> </div> </div> </div> <div class="ListI-slide"> <div class="PromoA" data-no-media data-image-align="top"> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.jobs/jobs/1205627/data-scientist-sponsored-brands-recommendations?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0">Data Scientist - Sponsored Brands Recommendations</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <ps-truncatable data-truncation-line-count="5" data-truncation-link-label="Read More" class="PromoA-description">Amazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.The Sponsored Brands Recommendations team is a versatile environment, with a wide variety of challenges. We focus on helping advertisers by providing recommendations to help them achieve their goals. We look at mega size data from both retail and advertising space, and coming up with ML based recommendations through multiple products.As a Data Scientist, you will solve real world problems by analyzing large amounts of business data, diving deep to identify business insights and opportunities, designing simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with scientists, engineers, BIE's, product managers. The successful candidate should have a strong quantitative background and excellent data analytics / math skills.Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation#sspa</ps-truncatable> </div> </div> </div> </div> </div> </ps-carousel><div class="ListH"> <div class="ListH-header-wrapper"> <h2 class="ListH-header">Academic engagements</h2><a class="ListH-header-button" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/academic-engagements" data-cms-ai="0">Learn More</a> </div> <ul class="ListH-items"> <li class="ListH-items-item"> <div class="PromoA" data-content-type="article" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Collaboration between Amazon and UC Berkeley advances AI and machine learning" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/academic-engagements/collaboration-between-amazon-and-uc-berkeley-advances-ai-and-machine-learning" data-cms-ai="0"> <img class="Image" alt="Inderjit Dhillon and Michael I. Jordan " width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/9dcfacc/2147483647/strip/true/crop/1440x807+0+0/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F7e%2F72%2F0fb883064ad9a432c22e6a5de817%2Fmichael-jordan-inderjit-dhillon-berkeley-bair-amazon.jpg"> </a> <div class="PromoA-media-credit">Credit: University of Texas at Austin, and Flavia Loreto </div> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/academic-engagements/collaboration-between-amazon-and-uc-berkeley-advances-ai-and-machine-learning" data-cms-ai="0">Collaboration between Amazon and UC Berkeley advances AI and machine learning</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 07, 2020</div> </div> <div class="PromoA-description">For two years now, Amazon has been collaborating with the University of California Berkeley Artificial Intelligence Research (BAIR) Lab, giving students the opportunity to work on challenging, real-world problems.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> <li class="ListH-items-item"> <div class="PromoA" data-content-type="blogPost" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Recipients of the 2019 Amazon Research Awards announced" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/recipients-of-the-2019-amazon-research-awards-announced" data-cms-ai="0"> <img class="Image" alt="2019 Amazon Research Award recipients ARA.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/770c3f5/2147483647/strip/true/crop/1201x673+0+3/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2Fb1%2Ff8%2F012253c848ce929c3a46b02a7565%2F2019-amazon-research-award-recipients-ara.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/blog/recipients-of-the-2019-amazon-research-awards-announced" data-cms-ai="0">Recipients of the 2019 Amazon Research Awards announced</a> </div> <div class="PromoA-details"> <div class="PromoA-date">June 17, 2020</div> </div> <div class="PromoA-description">Recipients represent 39 universities in 10 countries.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> </ul> </div><div class="ListH"> <div class="ListH-header-wrapper"> <h2 class="ListH-header">Videos and webinars</h2><a class="ListH-header-button" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/videos-webinars" data-cms-ai="0">View All</a> </div> <ul class="ListH-items"> <li class="ListH-items-item"> <div class="PromoA" data-content-type="article" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="AutoGluon Tabular: Automatic machine learning for tabular data" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/videos-webinars/autogluon-tabular-automatic-machine-learning-for-tabular-data" data-cms-ai="0"> <img class="Image" alt="smola_icml_noplay.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/0a87878/2147483647/strip/true/crop/2003x1123+0+0/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F93%2F23%2F63bf9042478b8eee1121c33faf1d%2Fsmola-icml-noplay.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/videos-webinars/autogluon-tabular-automatic-machine-learning-for-tabular-data" data-cms-ai="0">AutoGluon Tabular: Automatic machine learning for tabular data</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 17, 2020</div> </div> <div class="PromoA-description">Watch the keynote presentation by Alex Smola, AWS vice president and distinguished scientist, presented at the AutoML@ICML2020 workshop.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0">Machine learning</a> </div> </div> </div> </li> <li class="ListH-items-item"> <div class="PromoA" data-content-type="article" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Alexa & Friends features Dilek Hakkani-Tür, Alexa AI principal scientist" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/videos-webinars/alexa-friends-features-dilek-hakkani-tur-alexa-ai-principal-scientist" data-cms-ai="0"> <img class="Image" alt="Dilek_Alexa and friends.png" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/c42069b/2147483647/strip/true/crop/5001x2804+0+0/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F40%2F98%2F7cc70d1e4ecf9307d30e336ceb86%2Fdilek-alexa-and-friends.png"> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/videos-webinars/alexa-friends-features-dilek-hakkani-tur-alexa-ai-principal-scientist" data-cms-ai="0">Alexa & Friends features Dilek Hakkani-Tür, Alexa AI principal scientist</a> </div> <div class="PromoA-details"> <div class="PromoA-date">July 07, 2020</div> </div> <div class="PromoA-description">Tune in for the LIVE interview with Alexa evangelist Jeff Blankenburg.</div> <div class="PromoA-category"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0">Conversational AI / Natural-language processing</a> </div> </div> </div> </li> </ul> </div><div class="ListH"> <div class="ListH-header-wrapper"> <h2 class="ListH-header">Resources</h2> </div> <ul class="ListH-items"> <li class="ListH-items-item"> <div class="PromoA" data-content-type="section" data-image-align="top"> <div class="PromoA-media"> <a class="Link" aria-label="Around Amazon" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/around-amazon" data-cms-ai="0"> <img class="Image" alt="Around Amazon.jpg" width="535" height="300" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" 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href="https://web.archive.org/web/20200722111032/https://www.amazon.science/cloud-and-systems" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Cloud.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/94/b0/94affd2444f7a0d80227106f9211/cloud.svg"> </div> <div class="PromoD-title">Cloud and systems</div> <div class="PromoD-description">Developing new technologies that offer increased computing power, expanded database storage, faster content delivery, and other capabilities.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/computer-vision" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ComputerVision.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/9c/02/b5c9fb95439ebf5d4bcaef6fc4cd/computervision.svg"> </div> <div class="PromoD-title">Computer vision</div> <div class="PromoD-description">Helping devices see and understand our visual world.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/conversational-ai-natural-language-processing" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="ConversationalAI.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/fe/aa/910fd701416dabb6d3316fe2ec19/conversationalai.svg"> </div> <div class="PromoD-title">Conversational AI / Natural-language processing</div> <div class="PromoD-description">Building software and systems that help people communicate with computers naturally, as if communicating with family and friends.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/economics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Economics.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/a9/bc/ab88878c4faebca412cbef3b022b/economics.svg"> </div> <div class="PromoD-body"> <div 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data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="InfoManagement.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/4d/25/9ac984a8444e80d8071730edb6a0/infomanagement.svg"> </div> <div class="PromoD-title">Information and knowledge management</div> <div class="PromoD-description">Structuring the world’s information as it relates to everything available on Amazon.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/machine-learning" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="MachineLearning.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/93/06/f6c7a0ae49ec9d9427ce8dde796f/machinelearning.svg"> </div> <div class="PromoD-title">Machine learning</div> <div class="PromoD-description">Developing algorithms and statistical models that computer systems use to perform tasks without explicit instructions, relying on patterns and inference instead.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/operations-research-and-optimization" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Operations.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/65/a0/8603864b451fbce8ce61f0ca85e7/operations.svg"> </div> <div class="PromoD-title">Operations research and optimization</div> <div class="PromoD-description">Streamlining operations to deliver orders to you faster, more conveniently, and more economically.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/robotics" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Robotics.png" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/dims4/default/ff527f0/2147483647/strip/true/crop/282x282+22+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5d%2Fd1%2F7fd597ac49519be3e0ac1f990629%2Frobotics.png"> </div> <div class="PromoD-title">Robotics</div> <div class="PromoD-description">Delivering a faster and more consistent customer experience through a variety of robotic technologies.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/search-and-information-retrieval" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Search.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/0f/8a/4bf8055f47499b18da29af6b95c4/search.svg"> </div> <div class="PromoD-title">Search and information retrieval</div> <div class="PromoD-description">Developing advanced techniques to analyze behavioral patterns, lexical matches, and semantic matches to surface the most relevant recommendations in response to your queries.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" 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while giving you control over your information.</div> </div> </a> </div> </li> <li class="ListD-items-item"> <div class="PromoD" data-content-type="researcharea"> <a class="Link" href="https://web.archive.org/web/20200722111032/https://www.amazon.science/sustainability" data-cms-ai="0"> <div class="PromoD-media"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> <div class="PromoD-body"> <div class="PromoD-mediaThumbnail"> <img class="Image" alt="Sustainability.svg" width="295" height="295" loading="lazy" src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==" data-src="https://web.archive.org/web/20200722111032/https://assets.amazon.science/09/1d/d2ef27534875b71e1919bac64520/sustainability.svg"> </div> 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