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Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. 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! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon. Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team builds large-scale machine-learning solutions that delight customers with personalized and up-to-date recommendations that are related to their interests. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future. Key job responsibilities As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations, information retrieval and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Please visit https://www.amazon.science for more information.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The 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 enable our Retail and Marketplace businesses 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 ADSP Forecasting team's vision is to build the best in class forecasting products offered by any DSP to allow advertisers to forecast campaign outcomes across the full market funnel. Our goal is to empower advertisers using Amazon demand side platform to make informed decisions by providing predictions and recommendations of supply and ad-performance. Our forecasting models and analytical solutions will also help internal teams (sales, PSC, supply desk etc) to gain insights into forecasted supply, demand and ad performance to make the best business decisions. The team comprises scientists and engineers who own end-to-end projects - data collection, analysis, ideation, and prototyping, to development, metrics and monitoring. The models and services are integrated directly with Amazon's Ads eco system and the forecasts are used to drive key business decisions at the VP/SVP level. We are a team of Applied Scientists and Engineers, who are passionate about solving technical problems in the Ad Forecasting space with models using Machine Learning, Bayesian Statistics, etc. You will join a group of highly talented PhDs with diverse background to design, prototype, and implement models to deliver impact directly to customers. You will have the opportunity to present your work in science communities and to leadership As a Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - 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. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE

Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad 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 that leverage state of the art AI technologies. The Sponsored Products and Brands team is seeking a Principal Applied Scientist to lead the development and implementation of generative AI solutions for ad allocation and ranking on Amazon search pages. This role will be instrumental in revolutionizing how we match ads with customer intent and shopping behavior. Key job responsibilities * Design and develop novel generative AI architectures for real-time ad allocation, focusing on both efficiency and effectiveness at massive scale * Lead research initiatives in applying large language models and multimodal AI to understand deep semantic relationships between ads, queries, and user behavior * Create innovative approaches to leverage GenAI for dynamic ad placement optimization while maintaining strict latency requirements * Collaborate with cross-functional teams to integrate GenAI solutions into existing advertising systems * Author research papers and technical documentation, contributing to the broader scientific community

Are you excited about applying economic models and methods using large data sets to solve real world business problems? Then join the Economic Decision Science (EDS) team. EDS is an economic science team based in the EU Stores business. The teams goal is to optimize and automate business decision making in the EU business and beyond. An internship at Amazon is an opportunity to work with leading economic researchers on influencing needle-moving business decisions using incomparable datasets and tools. It is an opportunity for PhD students in Economics or related fields. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to work with large and complicated data sets. Knowledge of econometrics, as well as basic familiarity with Stata, R, or Python is necessary. Experience with SQL would be a plus. As an Economics Intern, you will be working in a fast-paced, cross-disciplinary team of researchers who are pioneers in the field. You will take on complex problems, and work on solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products. Roughly 85% of previous intern cohorts have converted to full time scientist employment at Amazon.

Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Data Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientists, product managers and engineers to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities -- Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience -- Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience. -- Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods). -- Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring. -- Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content. -- Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations. -- Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams. -- Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement. -- Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI. About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, transforming the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

The Supply Chain Optimization Technologies (SCOT) Buying team is at the heart of Amazon's global inventory management. We build sophisticated automated systems that decide what to buy, when to buy it, and where to place billions of dollars in inventory across Amazon's vast network. These decisions directly impact Amazon's ability to delight customers and drive operational efficiency. Join us to solve complex technical challenges at massive scale, shaping the core of Amazon's retail business through data-driven decisions. As a Data Scientist in SCOT Buying Outcomes, you will be responsible for developing and supporting best-in-class data science methodologies and models that provide crucial inputs to Amazon’s diverse buying programs. You’ll address ambiguous buying questions at scale by building tools drive key decisions in buying and sourcing strategies across Just in Time, Advanced Purchasing, and Global Ordering programs. This role requires exceptional technical expertise to handle massive datasets, familiarity with deriving causal inferences using observational data, and able to model variations related with different buying and cost scenarios across different planning horizons. Upon completion of statistical analysis, the Data Scientist needs to communicate results and recommendations to stakeholders by translating technical framework to business-oriented insights. This role requires an individual with excellent analytical abilities as well as business acumen. The successful candidate will be comfortable with ambiguity, with attention to detail, an ability to balance analysis with critical thinking and judgement, and work in a fast-paced and ever-changing environment. They recognize that the true measure of the success of the work product is based on the business impact the findings have had. Key job responsibilities - Collaborate with product managers and deep learning science and engineering teams to design and implement model solutions for Amazon buying systems - Develop edge case agile models for on-going buying assessments toward the end goal of optimizing buying decisions for millions of products world-wide - Use large datasets or experiments to make causal inferences or predictions - Work with engineers to automate science analysis processes and build scalable measurement solutions - Interpret data, write reports, and make actionable recommendations - Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. The candidate will need to be able to extract insights from data and be able to clearly communicate appropriate triggers and actions - Drive technical standards and best practices for the team's data architecture and analytics approaches - Mentor and provide technical guidance to other team members on complex projects A day in the life You might start your day working with a teammate to optimize a complex metric attribution logic. You could then collaborate with a Senior SDE to design the model architecture that enables our Gen AI tools for understanding the buying decisions. Later, you could lead a model backtesting and lab design review for a new cross-program framework and present analysis on a strategic business decision to senior leadership. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team You'll join a dynamic team of Data Scientists, Production Managers, SDEs, and BIEs within SCOT Buying Outcomes, focusing on data-driven decisions that impact Amazon's global supply chain. Our team brings together simulation and analytics across multiple buying programs, creating exciting opportunities to reshape our next generation of buying tools. We're passionate about making our models and data accessible and actionable, whether it's through self-service tools or deep-dive analyses. We value collaboration, innovation, and the ability to translate complex technical concepts into business impact.

Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Natural Language Processing (NLP), computer vision Large Language Models (LLM) and multi-modality? Are you interested in building Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds high performance AI systems using machine learning and deep learning that identify and prevent infringement and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our AI vision for Brand Protection. As a applied scientist on the team, you will use STOA AI and ML techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and own the end-to-end solution. An ideal candidate should be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied scientist, you will own the design and development of end-to-end AI solutions, from conception to launch in a rapidly evolving environment. You’ll have the opportunity to create science roadmaps, and drive production level projects that will support Amazon Science. extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. You will work closely with other scientists and enigneers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Use deep learning and machine learning techniques to create scalable solutions for business problems - Create business and analytics reports and present to the senior management teams - Research and implement novel AI solutions and publish research papers Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.

Economists at Amazon are expected to work directly with our senior management and scientists from other fields on key business problems faced across Amazon. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Collaborate with economists, data scientists, financial managers, and business leaders to define product requirements, provide science support, and communicate feedback. Implement economics methods to solve specific business problems utilizing code (Python, R, Scala, etc.). Improve existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. Presenting data in a format that is immediately useful to answer the critical business questions. About the team The Perfect Order Experience (POE) Econ team serves as POE teams' trusted economics partner, enhancing business strategy and operational effectiveness across POE and Selling Partner Services (SPS) through economic analysis and insights. We focus on advancing POE's goals towards the perfect order experience vision while delivering value to broader teams where strategic alignment exists. Through rigorous analytical frameworks, we help leaders navigate complex business and operational challenges. We embrace AI to revolutionize how we work and amplify our strategic contributions.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers