How Amazon achieved its 100% renewable energy goal

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srcset="https://assets.amazon.science/dims4/default/19b7219/2147483647/strip/true/crop/200x200+0+0/resize/295x295!/format/webp/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5b%2F15%2F48978dddf6afadbb113f76722397%2Fhow-amazon-achieved-its-100-percent-renewable-energy-goalqrcode"/><source width="295" height="295" data-image-size="squareMedium" srcset="https://assets.amazon.science/dims4/default/c7c36e0/2147483647/strip/true/crop/200x200+0+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5b%2F15%2F48978dddf6afadbb113f76722397%2Fhow-amazon-achieved-its-100-percent-renewable-energy-goalqrcode"/> <img class="Image" data-image-size="squareMedium" alt="https://www.amazon.science/news-and-features/how-amazon-achieved-its-100-percent-renewable-energy-goal" width="295" height="295" src="https://assets.amazon.science/dims4/default/c7c36e0/2147483647/strip/true/crop/200x200+0+0/resize/295x295!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F5b%2F15%2F48978dddf6afadbb113f76722397%2Fhow-amazon-achieved-its-100-percent-renewable-energy-goalqrcode" rel="nofollow" > </picture> </div> </div> </div> </div> </div> </div> </ps-action-bar> </div> </div> <div class="ArticlePage-articleContainer"> <div class="ArticlePage-articleBody"> <div class="ListArticleBody"> <div class="ListArticleBody-introduction RichTextBody"><p>Amazon recently <a class="Link" href="https://www.aboutamazon.com/news/sustainability/amazon-renewable-energy-goal" target="_blank" data-cms-ai="0" >announced</a> that we met our 100% renewable energy goal, seven years early. Making progress like that—especially with operations as complex as ours—isn’t easy, so we wanted to share more about how we were able to get it done. We used a variety of mechanisms, which included investing in new solar and wind projects, supporting projects in countries that still rely heavily on fossil fuels to power their grids (where renewable energy projects are needed the most), and purchasing Renewable Energy Certificates (RECs). </p><p>Here's a bit more about seven key steps we took to achieve our goal:</p></div> <ol class="ListArticleBody-items"> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Investing in 240+ utility-scale projects, which deliver new sources of energy to the grid</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>We signed agreements with developers and energy companies where we agreed to buy the renewable energy produced by hundreds of utility-scale solar and wind projects, which help make those projects possible and brings large amounts of new renewable energy online. The agreements – known as Power Purchase Agreements (PPAs) – give the developer confidence to buy materials, purchase land, and move forward with the construction. Once built, these projects provide new sources of renewable energy to the grid, helping decarbonize the grid mix – benefitting everyone who uses those grids (including us). In many cases, these projects would not have moved forward if it weren’t for our investment.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Enabling 270 onsite solar projects on Amazon buildings, which bring renewable energy directly to our buildings or the local grid</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>We invested in 270 solar arrays on the rooftops and grounds of Amazon fulfillment centers, Whole Foods Market stores, and other facilities. Many of these projects power the Amazon facilities directly, helping defray the amount of energy the buildings need from the grid. Other projects, like <a class="Link" href="https://www.aboutamazon.com/news/sustainability/amazons-solar-and-wind-projects-support-communities-throughout-the-southeastern-us" target="_blank" data-cms-ai="0" >the rooftop solar array</a> at the Amazon Air Hub at the Cincinnati/Northern Kentucky International Airport (CVG), sends power to the local grid, helping power nearby homes and businesses.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Bringing new renewable energy to regions where our operations are located</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>The majority of the utility-scale projects we invest in connect to grids where we have operations, including our data center regions. For example, in the IAD Region in Northern Virginia, Amazon has invested in 19 solar projects capable of producing a total of 1.3 gigawatts (GW) of renewable energy for the local grid. In our PDX Region in Oregon, Amazon <a class="Link" href="https://www.aboutamazon.com/news/aws/aws-data-centers-eastern-oregon?p=amazon-renewable-energy-commitments-will-bring-clean-power-to-eastern-oregon" target="_blank" data-cms-ai="0" >recently invested in Leaning Juniper</a>, a wind farm that is being repowered with enhanced turbine technology to help it produce more energy. In our DUB Region in Ireland, <a class="Link" href="https://www.datacenterdynamics.com/en/news/aws-to-build-data-centers-at-energy-park-in-irish-midlands/" target="_blank" data-cms-ai="0" >Amazon is collaborating</a> with Bord na Mona Energy park in County Offaly to co-locate data centers with wind projects, and to invest in up to 800 megawatts (MW) of renewable projects across the country.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Bringing new solar and wind projects to dirty grids</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>While a lot of our projects bring carbon-free energy to the grids where we have operations, we’re also focused on making the grid cleaner and more reliable for everyone. An emissions-first approach – which prioritizes supporting renewable energy projects in locations and countries that still rely heavily on fossil fuels – is the fastest way to decarbonize global grids. We’ve done this by investing in projects in countries including Poland, Greece, South Africa, and India, where we <a class="Link" href="https://www.aboutamazon.com/news/sustainability/renewable-energy-investment-india" target="_blank" data-cms-ai="0" >enabled 50 solar and wind projects</a> – enough to power 1.1 million homes in New Delhi each year. To demonstrate why location matters, by investing in seven utility-scale renewable energy projects in India, instead of a country like Sweden where the grid is already renewable-heavy, we’ve reduced carbon emissions by 18 times. And to encourage other corporate renewable energy buyers to do the same, we created the <a class="Link" href="https://www.emissionsfirst.com/" target="_blank" data-cms-ai="0" >Emissions First Partnership</a><i> </i>alongside many other large buyers of renewable energy, including General Motors, Intel, Meta, and Rivian.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Using grids that already have a large amount of renewable energy</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>We’re often able to locate projects on grids that already have a large amount of renewable energy, and as part of our renewable energy <a class="Link" href="https://sustainability.aboutamazon.com/renewable-energy-methodology.pdf" target="_blank" data-cms-ai="0" >methodology</a>, we count the renewable energy mix in the grid toward our goal. This means in a country like the U.S., where the grid already runs on 31% renewable energy, we’re able to reach 100% by investing in additional solar and wind projects to cover the remaining 69% of our energy consumption.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Purchasing Renewable Energy Certificates (RECs)</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>No company with complex and growing operations is able today to only consume renewable energy – there simply aren’t enough sources in enough locations, and it takes a while for new projects to come online. Like most companies with ambitious climate goals like ours, we also purchase RECs. RECs are used to legally substantiate claims of renewable energy use, and are used by many companies and government agencies, and other entities, like local utilities. They also help make renewable energy investment more inclusive by allowing medium and small businesses to invest in renewable energy projects without having to purchase an entire wind or solar farm, allowing them to also play a role in addressing climate change.</p><p>When Amazon or any other buyer purchases renewable energy, there’s no way to guarantee that the same electron generated by an Amazon-backed project will be the same electron consumed by our data centers, fulfillment centers, or other operations. RECs allow us to account for these electrons, which are still flowing through the grid, and helping power other needs, like energy to run homes and businesses.</p> </div> </div> </li> <li class="ListArticleBody-items-item" data-has-headline><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-headline">Using different kinds of RECs</div> <div class="ListArticleBodyItem-body RichTextBody"> <p>Amazon purchases “bundled” and “unbundled” RECs, which we use as a temporary measure. Bundled RECs are purchased alongside our investment in a wind or solar project, and act as a bridge until the project comes online. This is important, because due to grid constraints, many projects are delayed around the world. Across the United States, there are currently more than 260,000 megawatts (MW) of renewable energy and storage projects waiting to connect to the grid—enough carbon-free energy to power 63.3 million US homes.</p><p>Unbundled RECs are purchased independent of a project. The revenue typically supports an existing project, helping with repairs, upgrades and other needs. Both forms of RECs are a fundamental component of the global renewable energy market – and are key to our society’s transition to a carbon-free energy future. Many current renewable energy technologies would not have been financed nor have become operable without the support of REC purchases, <a class="Link" href="https://acore.org/resources/renewable-energy-certificates-the-currency-of-the-clean-energy-market/" target="_blank" data-cms-ai="0" >according to</a> the American Council on Renewable Energy.</p> </div> </div> </li> <li class="ListArticleBody-items-item"><div class="ListArticleBodyItem"> <div class="ListArticleBodyItem-body RichTextBody"> <h2><p>Amazon’s commitment to sustainability</p></h2><p>We are focused on reaching our Climate Pledge to be net-zero carbon by 2040. We know our path won’t be linear, and we’re continuing to innovate in order to add new sources of carbon-free energy to grids around the world.</p><p>We believe in transparency for our customers, employees and partners, and release a voluntary annual <a class="Link" href="https://www.aboutamazon.com/news/sustainability/amazon-sustainability-report-2023" target="_blank" data-cms-ai="0" >Sustainability Report</a> that highlights the work and progress we’re making to become a more sustainable company, across every business in which we operate. This report, including our achievement of our 100% renewable energy goal, is <a class="Link" href="https://sustainability.aboutamazon.com/reporting" target="_blank" data-cms-ai="0" >verified</a> by independent external third-party assurors.</p><div class="Enhancement" data-align-center-expanded> <div class="Enhancement-item"><div class="PromoBasic" data-media> <div class="PromoBasic-content"> <div class="PromoBasic-media"> <a class="Link" aria-label="Five ways Amazon is preparing for the energy demands of the future" href="https://www.amazon.science/news-and-features/five-ways-amazon-is-preparing-for-the-energy-demands-of-the-future" data-cms-ai="0" ><picture><source type="image/webp" width="768" height="496" data-image-size="promoBasic" 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data-cms-ai="0" >Five ways Amazon is preparing for the energy demands of the future</a></div> <div class="PromoBasic-description">From investing in new carbon-free energy projects to advocating for grid modernization and collaborating with key stakeholders around the world, Amazon is working toward a cleaner energy future.</div> </div> </div> </div> </div> </div> </div><p></p> </div> </div> </li> </ol> </div> </div> </div> <div class="ArticlePage-researchAreas"> <div class="ListTags" columnCount="3" > <div class="ListTags-title"> Research areas </div> <ul class="ListTags-items"> <li class="ListTags-items-item"> <a class="Link" href="https://www.amazon.science/research-areas/sustainability" data-cms-ai="0" >Sustainability</a> </li> </ul> </div> </div> <div class="ArticlePage-tags"> <div class="ListTags" columnCount="3" > <div class="ListTags-title"> Tags </div> <ul class="ListTags-items"> <li class="ListTags-items-item"> <a class="Link" href="https://www.amazon.science/tag/amazon-sustainability-report" data-cms-ai="0" >Amazon Sustainability Report </a> </li> <li class="ListTags-items-item"> <a class="Link" href="https://www.amazon.science/tag/renewable-energy" data-cms-ai="0" >Renewable energy </a> </li> <li class="ListTags-items-item"> <a class="Link" href="https://www.amazon.science/tag/the-climate-pledge" data-cms-ai="0" >The Climate Pledge </a> </li> </ul> </div> </div> <div class="ArticlePage-authors-about">About the Author</div> <div class="ArticlePage-authorInfoSection"> <div class="ArticlePage-authorInfo"> <div class="ArticlePage-authorInfo-bio"> <div class="ArticlePage-authorInfo-bio-name"> Staff writer </div> </div> </div> </div> </article> </main> <div class="Page-below" ><div class="ListB" data-add-divider columnCount="3" > <div class="ListB-header-wrapper"> <h2 class="ListB-header">Related content</h2> </div> <ul class="ListB-items" data-list-loadmore-items> <li class="ListB-items-item"> <div 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</div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://www.amazon.science/blog/removing-selection-bias-from-evaluation-of-recommendations" data-cms-ai="0" >Removing selection bias from evaluation of recommendations</a> </div> <div class="PromoA-details"> <div class="PromoA-authors"><a class="Link" href="https://www.amazon.science/author/ozalp-ozer" data-cms-ai="0" >Özalp Özer</a>, <a class="Link" href="https://www.amazon.science/author/serdar-simsek" data-cms-ai="0" >Serdar Şimşek</a></div> <div class="PromoA-date">October 21, 2024</div> </div> <div class="PromoA-description">Causal machine learning provides a powerful tool for estimating the effectiveness of Fulfillment by Amazon’s recommendations to selling partners.</div> <div class="PromoA-category"> <a class="Link" href="https://www.amazon.science/research-areas/operations-research-and-optimization" data-cms-ai="0" >Operations research and optimization</a> </div> </div> </div> </li> <li class="ListB-items-item"> <div class="PromoA" data-content-type="blog post" data-image-align="top" > <div class="PromoA-media"> <a class="Link" aria-label="The life of a prescription at Amazon Pharmacy" href="https://www.amazon.science/blog/the-life-of-a-prescription-at-amazon-pharmacy" data-cms-ai="0" ><picture><source type="image/webp" width="535" height="300" data-image-size="promoMedium" data-srcset="https://assets.amazon.science/dims4/default/3880c49/2147483647/strip/true/crop/12591x7060+0+11/resize/535x300!/format/webp/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F19%2Fb3%2Fe4b899d14056b58546dd2c81cda9%2Fpharmacy-workflow.png"data-lazy-load="true" srcset='data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZlcnNpb249IjEuMSIgaGVpZ2h0PSIzMDBweCIgd2lkdGg9IjUzNXB4Ij48L3N2Zz4='/><source width="535" height="300" data-image-size="promoMedium" data-srcset="https://assets.amazon.science/dims4/default/b08b209/2147483647/strip/true/crop/12591x7060+0+11/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F19%2Fb3%2Fe4b899d14056b58546dd2c81cda9%2Fpharmacy-workflow.png"data-lazy-load="true" srcset='data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZlcnNpb249IjEuMSIgaGVpZ2h0PSIzMDBweCIgd2lkdGg9IjUzNXB4Ij48L3N2Zz4='/> <img class="Image" data-image-size="promoMedium" alt="Pharmacy workflow.png" width="535" height="300" data-src="https://assets.amazon.science/dims4/default/b08b209/2147483647/strip/true/crop/12591x7060+0+11/resize/535x300!/quality/90/?url=http%3A%2F%2Famazon-topics-brightspot.s3.amazonaws.com%2Fscience%2F19%2Fb3%2Fe4b899d14056b58546dd2c81cda9%2Fpharmacy-workflow.png" data-lazy-load="true" src="data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZlcnNpb249IjEuMSIgaGVpZ2h0PSIzMDBweCIgd2lkdGg9IjUzNXB4Ij48L3N2Zz4="> </picture> </a> </div> <div class="PromoA-content"> <div class="PromoA-title"> <a class="Link" href="https://www.amazon.science/blog/the-life-of-a-prescription-at-amazon-pharmacy" data-cms-ai="0" >The life of a prescription at Amazon Pharmacy</a> </div> <div class="PromoA-details"> <div class="PromoA-authors"><a class="Link" href="https://www.amazon.science/author/alexandre-alves" data-cms-ai="0" >Alexandre Alves</a>, <a class="Link" href="https://www.amazon.science/author/anita-vila" data-cms-ai="0" >Anita Vila</a></div> <div class="PromoA-date">September 30, 2024</div> </div> <div class="PromoA-description">From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.</div> <div class="PromoA-category"> <a class="Link" href="https://www.amazon.science/research-areas/conversational-ai-natural-language-processing" data-cms-ai="0" >Conversational AI</a> </div> </div> </div> </li> </ul> </div><ps-carousel class="ListI" columnCount="3" > <div class="ListI-header-wrapper"> <h2 class="ListI-header">Work with us</h2><a class="ListI-header-button" href="https://www.amazon.science/careers" data-cms-ai="0">See more jobs</a> <a class="ListI-header-buttonDesktop" href="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://www.amazon.jobs/jobs/2840061/applied-scientist-sponsored-products-amazon-ads?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Applied Scientist, Sponsored Products, Amazon Ads</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Amazon continues to invest heavily in building our world class advertising business. 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, breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and strong 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 Products OSSR team is responsible for all non-search supply and associated experiences. As an Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful strategic initiatives, creating lasting value for Amazon and our advertising customers. Key job responsibilities • Support business, science and engineering strategy and roadmap for Sponsored Products OSSR projects • Drive alignment across organizations for science, engineering and product strategy to achieve business goals • Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers • Develop state of the art experimental approaches and ML models. About the team Sponsored Products (SP) is Amazon's largest and fastest growing business. Over the last few years we grown to a multi-billion dollar business. SP ads are shown prominently throughout search and detail pages, allowing shoppers to seamlessly discover products sold on Amazon. Ad experience and market place is one of the highest impact decisions we make. This role has unparalleled opportunity to grow our marketplace and deliver value for advertisers and shoppers.</div> </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://www.amazon.jobs/jobs/2840111/applied-scientist-machine-learning-accelerator?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Applied Scientist, Machine Learning Accelerator</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist II in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.</div> </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://www.amazon.jobs/jobs/2839736/applied-scientist-amazon?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Applied Scientist, Amazon</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">An information-rich and accurate product catalog is a strategic asset for Amazon. It powers unrivaled product discovery, informs customer buying decisions, offers a large selection, and positions Amazon as the first stop for shopping online. We use data analysis and statistical and machine learning techniques to proactively identify relationships between products within the Amazon product catalog. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality). Amazon’s Item and Relationship Identity Systems group is looking for an innovative and customer-focused applied scientist to help us make the world’s best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will work in a collaborative environment where you can experiment with massive data from the world’s largest product catalog, work on challenging problems, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers. Key job responsibilities * Map business requirements and customer needs to a scientific problem. * Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization. * Research, design and implement scalable machine learning (ML) techniques to solve problems that matter to our customers in an iterative fashion. * Design, experiment and evaluate highly innovative models for predictive, explainable learning * Partner with other scientists to build state-of-the-art ML systems powering Amazon * Work closely with software engineering teams to drive real-time model experiments, implementations and new feature creations * Stay informed on the latest machine learning, natural language and/or artificial intelligence trends and make presentations to the larger engineering and applied science communities. About the team The IRIS team owns programs and systems to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog. We focus on the following areas: 1) reducing customer perceived duplicates: eliminating all duplicate ASINs that are indistinguishable by customers and identifying broken and missing variations, 2) reducing product detail page inconsistency: preventing inconsistent item identities, and improving the customer experience by automatically detecting and creating factual relationships between ASINs: e.g. variation families, newer versions, 3) reducing selling partner listing friction: reducing GTIN defects in the catalog, and false conflicts in contributions, and 4) improving brand customer experience: providing a strong brand identity to contributions and ASINs, by matching them to Universal Brand Catalog brand entities.</div> </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://www.amazon.jobs/jobs/2840075/applied-scientist--amazon?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Applied Scientist , Amazon</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are 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 to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, 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</div> </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://www.amazon.jobs/jobs/2840082/genaiic-geo-leader-awsi-generative-ai-innovation-center?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >GenAIIC Geo Leader, AWSI, Generative AI Innovation Center</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, VA, Arlington</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Are you passionate about helping customers innovate and create transformative experiences? Do you want to be at the forefront of utilizing AI and ML services to drive innovation for thousands of AWS customers globally? And are you interested in building and leading high-performing teams in the fast paced area of generative AI? The AWS Generative AI Innovation Center (GenAIIC) is on a mission to accelerate production adoption of AWS generative AI services across global customers. This is an exciting opportunity to be part of a fast growing and entrepreneurial organization, bringing innovation to customers and growing the adoption of cloud services. The GenAIIC organization is staffed with specialized and experienced business strategists and ML scientists who solve complex problems for customers. We start with the customer and work backwards in everything we do. We believe that GenAI solutions, when founded in deep customer needs, can transform organizations, and produce groundbreaking experiences. We are a small, tight-knit team who value authentic, teammates that think creatively and will proactively seek out opportunities to advance the impact of the GenAIIC. As the GenAIIC Geo Leader, AWSI, you will be responsible for building and managing a team of generative AI strategists and ML scientists that are working with large multi-national customers to architect and implement innovative generative AI solutions. You will regularly engage with Director, VP, C-level customer executives. You will be responsible for building relationships, capturing opportunity, driving engagement, and delivering on business objectives. You must bring a strong blend of business and technical skills and lead all GenAIIC activities for AWS Industries. You are ready to roll-up your sleeves and work alongside the team in developing solutions when needed. You will lean on your experience working directly with customers, and are passionate in empowering these organizations to leverage generative AI and derive business outcomes. Key job responsibilities - Lead a high-performing team of business strategists, ML scientists, and generative AI domain experts - Guide the team in designing, developing, and evaluating innovative generative AI solutions to address customer issues - Advise and influence customers on technology decisions, including contrasting technology choices - Drive adoption of AWS generative AI services, delivering workload/solution specific domain expertise to the broader field organization, and developing repeatable, packaged solutions - Develop new strategies and mechanisms to address evolving customer needs, while driving higher business impact for AWS - Influence product roadmap with service teams to deliver value for customers and accelerate adoption About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.</div> </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://www.amazon.jobs/jobs/2838745/senior-applied-scientist-amazon?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Senior Applied Scientist, Amazon</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">We are seeking a motivated and experienced Senior Applied Scientist with expertise in Machine Learning (ML), Artificial Intelligence (AI), Big Data, and Service Oriented Architecture. You should have a deep understanding of the digital advertising business and scaled marketing across communication channels. In this role, you will collaborate with a cross-functional team of talented scientists and engineers to innovate, iterate, and solve real-world marketing problems with cutting-edge AWS technologies. You will lead in-depth analyses of the key problems faced by Amazon Ads customers and the challenges faced by marketing teams in meeting customer needs at scale. To address these problems, you will build innovative large-scale ML/AI solutions such as bespoke omni-channel recommender systems, and specialized LLM-powered assistants for customers and marketers. You will independently drive research and prototyping to deliver functional proofs of concept (POCs), and then partner with engineers to inform the technology roadmap and deploy successful POCs as scalable batch and real-time applications in production. Key job responsibilities • Define and execute a research and development plan that enables data-driven marketing decisions and delivers inspiring customer experiences • Evaluate, evolve, and invent scientific techniques to effectively address customer needs and business problems • Establish and drive science prototyping best practices to ensure coherence and integrity of data feeding into production ML/AI solutions • Collaborate with colleagues across science and engineering disciplines for rapid prototyping at scale • Partner with engineering teams to solve complex technical problems, define system-level requirements, develop implementation plans, and guide the adaptation of techniques to meet production needs • Partner with product managers and stakeholders to define forward-looking product visions and prospective business use-cases • Drive and lead of culture of data-driven innovation within and outside across Amazon Ads Marketing organization • Influence organizational vision across Ads Marketing organization About the team The Marketing Decisions Science team provides AI/ML products to enable Amazon Ads Marketing to deliver relevant and compelling guidance, education, and inspiration to prospective and active advertisers across marketing channels. We own the product, technology, and deployment roadmap for AI/ML products across Amazon Ads Marketing. We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.</div> </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://www.amazon.jobs/jobs/2838752/sr-data-scientist-generative-ai-innovation-center?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Sr. Data Scientist, Generative AI Innovation Center</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. This position requires that the candidate selected be a US Citizen. Key job responsibilities As an Data Scientist, you will - Collaborate with AI/ML scientists and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction A day in the life About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.</div> </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://www.amazon.jobs/jobs/2839825/applied-scientist-sponsored-products?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Applied Scientist, Sponsored Products</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Amazon Ads is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Bespoke Shopping Experience team within SP develops customer facing experiences and machine learning models to better understand and address the diverse needs and behaviors of various shopper cohorts. As an Applied Scientist on the team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches.</div> </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://www.amazon.jobs/jobs/2839664/senior-research-scientist-aigc-science-and-analytics?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Senior Research Scientist, AIGC Science and Analytics</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, NY, New York</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">The PXT (People Experience and Technology) Science and Analytics team for AIGC (Ads, IMDb and Grand Challenge) is seeking a highly skilled and motivated Senior Research Scientist to join our team. You will be leading Research Science space to support the AIGC PXT org initiatives. If you enjoy innovating, thinking big and want to contribute directly to the success of a growing team, you may be a prime candidate for this position. Key job responsibilities In this role you will: Design experiments, test hypotheses, and build actionable models Conduct quantitative analyses of talent management data and trends Conduct qualitative data collection and analysis Partner closely and drive effective collaborations across multi-disciplinary research and product teams Consult on appropriate analytic methodologies and scope research requests</div> </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://www.amazon.jobs/jobs/2838848/research-scientist-prime-video?cmpid=bsp-amazon-science" target="_blank" data-cms-ai="0" >Research Scientist, Prime Video</a> </div> <div class="PromoA-details"> <div class="PromoA-location">US, WA, Seattle</div> </div> <div data-truncation-line-count="5" data-truncation-link-label="Read more" class="PromoA-description">Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. On Prime Video, customers can find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies Road House, The Lord of the Rings: The Rings of Power, Fallout, Reacher, The Boys, and The Idea of You; licensed fan favorites Dawson’s Creek and IF; Prime member exclusive access to coverage of live sports including Thursday Night Football, WNBA, and NWSL, and acclaimed sports documentaries including Bye Bye Barry and Federer; and programming from partners such as Apple TV+, Max, Crunchyroll, and MGM+ via Prime Video add-on subscriptions, as well as more than 500 free ad-supported (FAST) Channels. Prime members in the U.S. can share a variety of benefits, including Prime Video, by using Amazon Household. Prime Video is one benefit among many that provides savings, convenience, and entertainment as part of the Prime membership. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles, including blockbusters such as Challengers and The Fall Guy, via the Prime Video Store, and can enjoy content such as Jury Duty and Bosch: Legacy free with ads on Freevee. Customers can also go behind the scenes of their favorite movies and series with exclusive X-Ray access. For more info visit www.amazon.com/primevideo. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As a Research Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), natural language processing (NLP), multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s recommendation systems, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: • Lead cutting-edge research in computer vision and natural language processing, applying it to video-centric media challenges. • Develop scalable machine learning models to enhance media asset generation, content discovery, and personalization. • Collaborate closely with engineering teams to integrate your models into production systems at scale, ensuring optimal performance and reliability. • Actively participate in publishing your research in leading conferences and journals. • Lead a team of skilled research scientists, you will shape the research strategy, create forward-looking roadmaps, and effectively communicate progress and insights to senior leadership • Stay up-to-date with the latest advancements in AI and machine learning to drive future research initiatives.</div> </div> </div> </div> </div> </div> </ps-carousel></div> </div> <ps-footer class="Page-footer"> <div class="Page-footer-body"> <div class="Page-footer-logo"><a aria-label="home 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