Careers

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their macroeconomics and forecasting skillsets to solve real world problems. The intern will work in the area of forecasting, developing models to improve the success of new product launches in Private Brands. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis About the team The Amazon Private Brands Intelligence team applies Machine Learning, Statistics and Econometrics/economics to solve high-impact business problems, develop prototypes for Amazon-scale science solutions, and optimize key business functions of Amazon Private Brands and other Amazon orgs. We are an interdisciplinary team, using science and technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon, covering areas such as pricing, discovery, negotiation, forecasting, supply chain and product selection/development.

Amazon’s Modeling and Optimization (MOP) Team is looking for a passionate individual with strong optimization and analytical skills to join us in the endeavor of designing and improving the most complex transportation and fulfillment network in the world. The team is responsible for optimizing the global transportation and fulfillment network for Amazon.com and ensuring that the company is able to deliver our customers’ products to them as quickly, accurately, and cost effectively as possible. We design the network that delivers products from vendors and sellers to end customers, through both Amazon’s internal network as well as external partners, using multiple transportation modes. Optimizing the end-to-end network requires deep understanding of inventory management, placement, transportation, and supply chain management. Only through innovative and strategic thing, we will make the right capital investments in technology, buildings and equipment that allows for long-term success. Key job responsibilities We are seeking an experienced scientist who has a solid background in Operations Research, Supply Chain Management, Applied Mathematics, or other similar domain. In this role, you will develop and deploy models and tools that are innovative and scalable to solve new challenges in Amazon's global fulfillment network. You will collaborate with other scientists across teams to create integrated solutions that improves fulfillment speed, cost, and carbon emission. You have deep understanding of business challenges and provide scientific analysis to support business decision using a range of methodologies. You design science tool platforms, deploy models, create data pipelines, or simplify existing processes. About the team https://www.linkedin.com/feed/update/urn:li:activity:7089317294417346561/

The WW Operations IPAT team is revolutionizing Amazon's financial forecasting through TrendCast, an innovative, automated, science-based top-down forecast modeling that's transforming how we predict Worldwide Operations costs. This innovation approach leverages key performance indicators to generate automated, transparent forecasts with unprecedented frequency. By moving beyond traditional bottom-up planning, TrendCast empowers leadership with real-time insights, enabling swift identification of both risks and opportunities. As our operational scope rapidly expands into Generative AI, we are also building an intelligent, GenAI-powered Finance Knowledge Base to further reduce the workload on finance teams and facilitate leadership’s decision-making process. We are seeking a driven Data Scientist to help build out these advanced analytical and AI-driven solutions. Key job responsibilities In this role, you will be a core contributor to our data science initiatives, working at the intersection of traditional machine learning and Generative AI. You will work closely with senior scientists, engineering, and finance stakeholders to translate complex business problems into scalable models. Your work will directly impact our financial forecasting accuracy (TrendCast) and help develop intuitive, LLM-powered tools that allow finance teams to query, synthesize, and extract insights from our extensive financial knowledge base. A day in the life - Develop, train, and evaluate machine learning and statistical models for financial forecasting, ensuring solutions are scalable for large-scale operational challenges. - Design and implement Generative AI applications, specifically building and optimizing Retrieval-Augmented Generation (RAG) pipelines and LLM-based agents to power our internal Finance Knowledge Base. - Drive modeling projects from data exploration and feature engineering to model deployment and monitoring, working collaboratively with both technical and non-technical stakeholders. - Build and maintain robust data pipelines, utilizing distributed computing frameworks to process and analyze petabyte-scale financial and operational datasets. - Develop a deep understanding of key business metrics and KPIs, connecting model outputs to actionable levers that inform strategic operational decisions. - Collaborate closely with finance, product, and BIE teams to deploy models, gather feedback, and continuously iterate on both forecasting algorithms and GenAI user experiences.

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! The Prime Video Title Lifecycle Presentation team sits at the intersection of science, experimentation, and customer experience. We leverage data signals and rigorous testing to present the most engaging information about our content to customers at precisely the right moment. Our mission is to ensure every customer interaction with Prime Video content is informed, relevant, and compelling in order to drive discovery and engagement across our vast catalog. We're seeking a Sr. Applied Scientist who excels at building sophisticated machine learning systems for content presentation and discovery. The ideal candidate brings deep expertise in: - Multi-modal embeddings for rich metadata representation, enabling nuanced understanding of content attributes and customer preferences - Contextualized ranking systems that adapt to customer intent, viewing context, and real-time signals - Reinforcement learning frameworks that create continuous improvement loops, allowing our systems to learn and optimize from customer interactions over time - General modeling techniques with strong fundamentals in machine learning and statistical methods - Recommender systems experience, with proven ability to build and scale personalization solutions You'll work with technology to solve complex problems in content discovery, leveraging large-scale data to create experiences that delight millions of Prime Video customers worldwide. Key job responsibilities - Lead Cross-Functional Science Initiatives: Drive a diverse portfolio of applied science projects spanning recommender systems, generative AI agent development and evaluation across multiple modalities, and computer vision applications. Demonstrate both breadth of understanding across technical domains and sufficient depth in each area to effectively lead multiple concurrent initiatives to successful outcomes. - Bridge Science and Engineering for Production-Scale Deployment: Partner with engineering teams to productionize machine learning models at Prime Video scale. Develop production-ready science code that meets engineering standards for performance, reliability, and maintainability, ensuring seamless transition from research to deployment. - Mentor and Develop Technical Talent: Provide technical mentorship and guidance to junior scientists and engineers on applied science methodologies, best practices, and professional development. Foster a culture of scientific rigor and continuous learning within the team.

About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions. As an Applied Scientist on this 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. 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.

Are you passionate about leveraging data and economics to enhance customer experience across Amazon's diverse businesses? The Customer Experience and Business Trends (CXBT) organization is seeking an Economist to join our Benchmarking Economics Analytics and Measurement (BEAM) team. Our mission is to drive customer experience improvements through innovative economic modeling, advanced analytics, and scalable scientific solutions. As an Economist on our team, you will collaborate with senior management, business stakeholders, scientists, engineers, and economics leadership to solve complex business challenges across Amazon's business lines. You'll develop sophisticated econometric models using our world-class data systems, applying diverse methodologies spanning causal inference, machine learning, and generative AI. In this fast-paced environment, you'll tackle challenging problems that directly influence strategic decision-making and drive measurable business impact. Key job responsibilities - Develop economic theory and deliver causal machine learning models at scale - Collaborate with cross-functional teams to translate research into scalable solutions - Write effective business narratives and scientific papers to communicate to both business and technical audiences - Drive data-driven decision making to improve customer experience About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

We are looking for an Economist to work on exciting and challenging business problems related to Amazon Retail’s worldwide product assortment. You will build innovative solutions based on econometrics, machine learning, and experimentation. You will be part of a interdisciplinary team of economists, product managers, engineers, and scientists, and your work will influence finance and business decisions affecting Amazon’s vast product assortment globally. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities * Work on a challenging problem that has the potential to significantly impact Amazon’s business position * Develop econometric models and experiments to measure the customer and financial impact of Amazon’s product assortment * Collaborate with other scientists at Amazon to deliver measurable progress and change * Influence business leaders based on empirical findings

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Calling all inventors to work on exciting new opportunities in Sponsored Products! You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across Amazon stores worldwide. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities - Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Calling all inventors to work on exciting new opportunities in Sponsored Products. We are a highly motivated, collaborative and fun-loving group with an entrepreneurial spirit and bias for action. You will join a newly-founded team with a broad mandate to experiment and innovate, with a focus on driving growth of sponsored products ad experiences across Amazon stores worldwide. This broad charter gives us the flexibility to explore and apply scientific techniques to novel product problems. You will have the satisfaction of seeing your work improve the experience of millions of Amazon shoppers worldwide while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills, and be a science leader in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities - Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship.

The Annapurna ML team is looking for a Senior Applied Scientist to work on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in our state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, Inferentia and Trainium, which represent the forefront of Annapurna innovation for advanced ML capabilities, and is the underpinning of Generative AI. As a Senior Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will architect and implement business-critical tooling, publish research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted scientist, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role. A background in machine learning and AI accelerators is preferred but not required. A day in the life Diverse Experiences Amazon 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 Amazon? 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 Amazon, 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 (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 in the cloud.