Careers

Project Leo (former Kuiper) is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of Ka band and FR1 band communication payload and customer terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology at global scale. The team develops and designs the communication system for project Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced physical layer + protocol stacks systems as proof of concept and reference implementation to improve the performance and reliability of the LEO network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Are you interested in recommendation systems that deliver the most enjoyable content to millions of customers? Do you want to invent new ways to seamlessly connect Kids and Parents through books, videos, apps, and more across a growing number of devices? If that sounds like you, then come join the Amazon Kids+ Personalization team! Join a team on a mission to make Kids+ every child's favorite destination to independently create, explore, and learn — and give parents the confidence to let them. Learn more at http://www.amazon.com/kids. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers (SDEs, DEs). You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team We're a team of experienced engineers and builders who are genuinely passionate about what we make — and who we make it for. Many of us are parents ourselves, and all of us share a deep belief that kids deserve technology that's both safe and genuinely fun. That tension — between delight and trust, between independence and guardrails — is the creative challenge that gets us out of bed in the morning.

The Returns and Recommerce Economics & Intelligence team advances returns science to maximize efficiency in returns processes while enhancing customer experience. We bring together economists, analysts, and engineers who leverage methodologies including timeseries econometrics, structural modeling, machine learning, and data science to deliver actionable insights. Our work spans the entire returns value chain – from understanding customer behavior to optimizing recommerce strategies or warehouse operations. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their timeseries and macro-econometrics skillsets to solve real world problems. The intern will work in Returns and Recommerce Economics developing macro models to assess impacts of macro shocks on customer returns. 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. Key job responsibilities 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. A day in the life

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. 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 WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.

Are you interested in leading growth initiatives for one of Amazon’s most significant and fastest growing businesses? Selling Partners offer hundreds of millions of unique products and are a critical to delivering on our vision of offering the Earth’s largest selection and lowest prices. The Amazon Marketplace enables over 2 million third-party selling partners in eleven marketplaces to list their products for sale to Amazon customers across the world. Within our WW Marketplace business, International Seller Services (ISS) oversees the recruiting and development of Selling Partners for all of our international marketplaces (e.g. UK, Germany, Japan, Middle East etc.). ISS also enables global selling, helping Sellers in one country expand and sell internationally. Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, the Central Science Team of Amazon's International Seller Services has an exciting opportunity for you as an Applied Science Manager. We are seeking an experienced science leader who is adept at a variety of skills; especially in generative AI, computer vision, and large language models that will help international sellers succeed as they sell on Amazon. The right candidate will provide science leadership, establish the right direction and vision, build team mechanisms, foster the spirit of collaboration and innovation within the org, and execute against a roadmap. This leader will provide both technical direction as well as manage a sizable team of scientists. They will need to be adept at recruiting, launching AI models into production, writing vision/direction documents, and building team mechanisms that will foster innovation and execution. Additionally, while the position is based in Seattle, this leader will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Key job responsibilities Key job responsibilities Responsibilities include: * Drive end-to-end applied science projects that have a high degree of ambiguity, scale, complexity. * Provide technical / science leadership related to NLP, computer vision and large language models. * Research new and innovative machine learning approaches. * Recruit high performing Applied Scientists to the team and provide mentorship. * Establish team mechanisms, including team building, planning, and document reviews. * Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE We are seeking a Data Scientist to own our causal inference infrastructure and drive sophisticated modeling that measures the incremental impact of business decisions. This role requires deep expertise in advanced causal inference methodologies—including synthetic control methods, Synthetic Difference-in-Differences (SDID), and Bayesian approaches—to design rigorous experiments, estimate long-term customer behavior effects, and translate complex analytical results into clear business recommendations. You will own the development and continuous improvement of these causal inference models while being responsible for machine learning operations at scale to ensure our organization makes data-driven decisions with confidence. At Audible, you will have an opportunity to make the best of your skillsets to both develop advanced scientific solutions and drive critical customer and business impact. You will play a key role to drive end-to-end solutions from understanding our business and business requirements, identifying opportunities from a large amount of historical data and engaging in research to solve the business problems. You'll seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders. You will be at the heart of an agile and growing area at Audible. ABOUT THE TEAM Audible Data Scientists are members of a global interdisciplinary insights and research team with an integral role in the design and integration of models to automate decision making throughout the business in every country. We empower the machine learning and deep learning techniques in many areas of the business. We translate business goals into agile, insightful analytics and seek to create value for both stakeholders and customers and convey findings in a clear, actionable way to managers and senior leaders. As a Data Scientist, you will... - Design and execute geo-level randomized experiments to measure incremental impact - Apply statistical techniques to evaluate causal impact in quasi-experimental settings - Ensure experiments are statistically valid by evaluating sampling strategies, statistical power, and potential sources of bias - Develop models that estimate long-term effects from short-term experiments using machine learning - Estimate how changes in customer behavior persist and decay over time - Own and maintain the geo-testing codebase, including deployment and scalability - Implement machine learning models at scale with focus on performance optimization - Partner with stakeholders to ensure models align with real business dynamics - Engage deeply with business problems through curiosity-driven questioning and brainstorming - Translate experimental results into financial impact and investment recommendations - Analyze marginal and average revenue impacts relative to costs - Communicate complex quantitative ideas clearly to non-technical stakeholders - Demonstrate understanding of Audible's business model and customer experience ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Economist III Job Location: Jersey City, New Jersey Job Number: AMZ9674161 Position Responsibilities: Work with the chief economist and senior management on key business problems faced in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, or operations. Apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising, and other areas. Build econometric models using data systems. Apply economic theory to solve business problems. Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. Apply tools from applied micro-econometrics (e.g. experimental design, difference-in-difference, regression discontinuity, and IV) and forecasting (essential time series models). Leverage big data tools for data extraction. Write up and present analysis for distribution to various levels of management at Amazon. Gain experience in academic research. Use program evaluation, forecasting, time series, panel data, and high dimensional problems. Use R and Stata. Position Requirements: Ph.D. or foreign equivalent degree in Economics, Finance, or a related field and three years of research or work experience in the job offered or a related occupation. Must have at least one year of research or work experience in the following skill(s): (1) working with Causal inference techniques (Difference-in-Differences, Matching, Double Machine Learning, Instrumental Variables, and Regression Discontinuity Designs); (2) statistical analysis tools (Python, R or Stata); (3) Data querying languages (SQL). Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $175,100/year to $236,900/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Manager III, Economist Job Location: New York, New York Job Number: AMZ9782156 Position Responsibilities: Support the measurement of the Alexa business and provide actionable insights across Alexa customers and devices. Work with product managers, SDEs, financial analysts, and BIEs to help the Alexa organization identify new features and business opportunities as well as drive optimization of current features and services through your analyses as the technical lead on the team. Own the development of econometric models, and manage the modelling and validation work for analysis products. Design and develop Econometric models to solve business problems and improve customer CX. Develop techniques to process large datasets, address quantitative problems, and contribute to design of automated systems around the company. Write high quality code and participating in Econ tech reviews, work with the business stakeholders to understand and solve their business problems by applying the frontier of economic thinking. Mentor and support junior Economists and scientists. Position Requirements: PhD degree or foreign equivalent in Economics, Computer Science, or related field and five years of research or work experience in the job offered or related occupation. Must have one year of research or work experience in the following skill(s): experience with casual inference and predictive modeling; experience in econometrics (program evaluation, forecasting, time series, panel data, and high dimensional problems); and experience with economic theory and quantitative methods. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $226,782/year to $260,500/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

Do you enjoy solving challenging problems and driving innovations in research? Are you seeking for an environment with a group of motivated and talented scientists like yourself? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? Do you want to play a key role in the future of Amazon transportation and operations? Come and join us at Amazon's Modeling and Optimization team (MOP). Key job responsibilities A Research Scientist in the Modeling and Optimization (MOP) team - provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques. - collaborates effectively with Amazon internal business customers, and is their trusted partner - is proactive and autonomous in discovering and resolving business pain-points within a given scope - is able to identify a suitable level of sophistication in resolving the different business needs - is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed - is aware of the limitations of their proposed solutions and is proactive in communicating them to the business, and advances the application of sciences towards Amazon business problems by bringing new methods, ideas, and practices to the team and scientific community. A day in the life - Your will be developing model-based optimization, simulation, and/or predictive tools to identify and evaluate opportunities to improve customer experience, network speed, cost, and efficiency of capital investment. - You will quantify the improvements resulting from the application of these tools and you will evaluate the trade-offs between potentially competing objectives. - You will develop good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, and business leadership. About the team - At the Modeling and Optimization (MOP) team, we use mathematical optimization, algorithm design, statistics, and machine learning to improve decision-making capabilities across WW Operations and Amazon Logistics. - We focus on transportation topology, labor and resource planning for fulfillment facilities, routing science, visualization research, data science and development, and process optimization. - We create models to simulate, optimize, and control the fulfillment network with the objective of reducing cost while improving speed and reliability. - We support multiple business lanes, therefore maintain a comprehensive and objective view, coordinating solutions across organizational lines where possible.

What does it take to build a foundation model that can forecast demand for hundreds of millions of products — including ones that have never been sold before? At Amazon, our Demand Forecasting team is tackling one of the most ambitious challenges in applied time series research: designing and building large-scale foundation models that generalize across an enormous and diverse catalog of products, geographies, and business contexts. This is not incremental modeling work. We are redefining what's possible in demand forecasting through novel architectures, training strategies, and data generation techniques. Our team operates at a scale that is unmatched in industry or academia. You'll design experiments across millions of products simultaneously, developing new model architectures and training methodologies that push the boundaries of what foundation models can learn from vast, heterogeneous time series data. You'll explore techniques in transfer learning, zero-shot forecasting, and synthetic data generation. The models you design here will ship to production and directly influence hundreds of millions of dollars in automated inventory decisions every week. Beyond operational impact, you'll publish your work at top-tier conferences and contribute to advancing the state of the art in time series foundation models for the broader scientific community. If you are a scientist who wants to work at the frontier of time series research, design novel solutions to problems no one else has solved at this scale, and see your research deployed to real-world impact — this is the team for you. Key job responsibilities 1. Design and implement novel deep learning architectures (e.g., Transformers, SSMs, or Graph Neural Networks) for time-series foundation models that generalize across hundreds of millions of products and diverse global contexts. 2. Drive the full development cycle - from whiteboarding new algorithmic approaches to overseeing production-scale deployments. 3. Collaborate with SDEs to build high-performance, distributed training and inference pipelines; translate complex scientific concepts into scalable, production-grade code in Python and Scala. 4. Leverage and develop agentic GenAI workflows to automate the end-to-end research cycle from synthesizing state-of-the-art literature and auto-generating experimental code to rapidly iterating on model architectures across millions of products. 5. Maintain a high bar for scientific excellence by publishing novel research in top-tier venues (e.g., NeurIPS, ICLR, KDD) and contributing to Amazon’s internal patent and science community. A day in the life No two days look the same, but most will involve a high-velocity blend of deep architectural work, distributed system design, and frontier scientific thinking at a scale you won’t find anywhere else. You might start the morning by designing a synthetic data pipeline to stress-test your foundation model. You’ll use generative techniques to simulate rare "black swan" supply chain events, ensuring your model remains robust where historical data is thin. You'll then lead a Scientific Design Review, walking senior leaders through your model’s architecture, defending your choice of loss functions with data-driven rigor. You’ll write high-performance code often paired with AI-coding assistants to handle the heavy lifting of boilerplate and unit testing. You’ll collaborate across a "Two-Pizza Team" of scientists and engineers, pushing the boundaries of research with a clear goal: contributing to work that will be published at top-tier venues (ICLR, NeurIPS) while simultaneously driving multi-million dollar automated decisions. The work is hard, the math is complex, and the tools are state-of-the-art. If you want to build the models that actually ship—this is where you do it. About the team The Demand Forecasting team sits at the heart of Amazon's supply chain, building the science that determines what products are available, when, and at what cost — for hundreds of millions of customers around the world. Our mission is to push the frontier of what's possible in large-scale time series forecasting, and to deploy that science where it creates real, measurable impact. We are a team of scientists who care deeply about both research rigor and real-world outcomes. We don't just publish — we ship. And we don't just ship — we measure, iterate, and raise the bar. Our work spans the full lifecycle: from foundational research and large-scale experimentation to production deployment and downstream impact measurement across supply chain, inventory, and financial planning.