Careers

Fulfillment by Amazon (FBA) is at the core of Amazon’s “Supply Chain by Amazon” vision, enabling hundreds of thousands of Selling Partners to leverage our world-class fulfillment network. FBA helps sellers in 130+ countries send products into our EU network and deliver to customers in 185+ countries, contributing to billions of units shipped in Europe each year. The FBA EU Analytics team is looking for a Senior Data Scientist to own high-impact BI, science and AI initiatives that shape the future of FBA in Europe. You will develop scalable AI solutions — including machine learning models, causal inference frameworks, and optimization algorithms — and deploy them to production to improve seller experience, ensure compliance, and optimize our end-to-end fulfillment economics (cost, speed, and quality). You will partner with Product, Tech, Operations, Finance, and Legal/Compliance across EU and WW to turn ambiguous business problems into well-framed scientific questions and productionized solutions. This is a high-visibility role with direct exposure to senior leadership and the opportunity to work with some of the world’s richest supply chain and marketplace datasets. Key job responsibilities As a Senior Data Scientist in FBA EU Analytics, you will: Own end-to-end science solutions : o Translate highly ambiguous, complex business problems into clear scientific hypotheses and success metrics. o Drive projects from concept and data discovery through model development, experimentation, deployment, and post-launch monitoring. Build advanced ML / AI / GenAI models o Develop predictive and prescriptive models for demand and volume forecasting, cost-to-serve, risk and fraud detection, and inventory / placement optimization. o Apply causal inference, uplift modeling, and experimentation frameworks to quantify the impact of new policies, tools, and FBA programs. o Leverage Generative AI and LLMs for use cases such as intelligent seller insights, document understanding for compliance, automated reasoning over large datasets, and AI-assisted decision support for internal stakeholders. Shape the AI & Analytics roadmap for FBA EU o Define and drive the Analytics, Data Science, and AI strategy for EU FBA. o “Look around corners” to proactively identify where science and GenAI can create step-change improvements in seller experience, compliance, and operational efficiency. o Prioritize opportunities based on impact, feasibility, and alignment with FBA and Supply Chain by Amazon strategy. Partner closely with engineering and data teams o Collaborate with Scientists, Data Engineers, BIEs, and SDEs to design data models, feature pipelines, and scalable science services (batch and real-time). o Help define and improve data quality, observability, and model monitoring standards across the team. Drive experimentation and decision science at scale o Design and analyze A/B tests and quasi-experiments to evaluate new policies, product features, and operational changes across EU marketplaces. o Build reusable experimentation and measurement frameworks for the wider FBA organization. Influence through narrative and storytelling o Create clear, concise documents and visualizations that “tell the story” of your findings to senior leaders and non-technical stakeholders. o Recommend actions and trade-offs, and influence roadmap and investment decisions using data. o Provide strategic technical guidance to L7+ business partners. Raise the bar for science excellence o Mentor other scientists, BIEs, and analysts on methodology, code practices, and stakeholder engagement. o Create and deliver best practice recommendations, blog posts, and presentations adapted to technical, business, and executive stakeholders. o Promote best practices in reproducible research, model governance, and documentation. A day in the life • Start your day reviewing dashboards for a recently launched GenAI-powered insights tool for Sellers, checking performance, drift, and business KPIs. • Join a working session with Product and Operations to refine problem statements for a new initiative to optimize cross-border inbound flows and FBA fees using a mix of forecasting, optimization, and causal inference. • Spend focused time in code exploring new features and model architectures, leveraging AWS services to accelerate EDA, documentation, and hypothesis generation. • Meet with a Data Engineer to iterate on a new data pipeline that will serve both your models and EU leadership reporting. • Draft the architecture of a new ML model that optimizes the fee rate card for EU FBA Sellers across hundreds of product categories and marketplaces. • Contribute to the MBR document with a summary of EU FBA AI Task Force deliverables from the past month. • Present a new code review best practice to the EU FBA Analytics team and clarify adoption expectations. About the team The FBA EU Analytics team sits at the intersection of science, analytics, and product for the FBA business in Europe. We: • Own core metrics and analytical foundations used by EU and WW leadership to steer the FBA business. • Develop scalable ML, GenAI, and BI solutions that simplify cross-border listing, inbound processes, compliance, and the fulfillment experience for Selling Partners and customers. • Work across EU and global stakeholders in Product, Tech, Operations, Finance, and Legal/Compliance, providing a holistic view of the FBA business. You will join a diverse group of Data Scientists, Business Intelligence Engineers, and Data Engineers who are passionate about combining rigorous science with pragmatic delivery and measurable business impact.

Are you passionate about leveraging data to deliver actionable insights that impact daily marketing activities at Amazon? The Customer Targeting team in Amazon is seeking an Applied Scientist to join our team to develop models for optimizing the performance of Amazon’s marketing initiatives across channels and advertising formats. You have experience applying modern machine learning methods to answer key business questions, make strategic and tactical recommendations for change, and work with business leaders to drive these to production. You are entrepreneurial and able to work in a highly collaborative environment. This role requires an individual with strong quantitative modeling skills and experience using statistical methods. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment. You will be expected to: - Leverage knowledge of statistics and optimization to frame decision-making problems for determining marketing spends across channels. - Predict future customer behavior and business conditions through machine learning and predictive modeling. - Use analytical and predictive techniques to build models for optimizing targeting. - Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.

Are you passionate about robotics and research? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. We’re looking for current PhD students with a passion for robotic research and applications to join us as Robotics Applied Scientist II Intern/Co-ops in 2026 to shape the future of robotics and automation at an unprecedented scale across. For these positions, our Robotics teams at Amazon are looking for students with a specialization in one or more of the research areas in robotics such as: robotics, robotics manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector), autonomous mobile robots, mobile manipulation, movement, autonomous navigation, locomotion, motion/path planning, controls, perception, sensing, robot learning, artificial intelligence, machine learning, computer vision, large language models, human-robot interaction, robotics simulation, optimization, and more! We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2026) opportunities across various Robotics teams at Amazon with different robotics research focus, with internship positions available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Amazon intern and co-op roles follow the same internship structure. "Intern/Internship" wording refers to both interns and co-ops. Amazon internships across all seasons are full-time positions, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. The robotics internship join dates, length, location, and prospective team will be finalized at the time of any applicable job offers. In your application, you will be able to provide your preference of research interests, start dates, internship duration, and location. While your preference will be taken into consideration, we cannot guarantee that we can meet your selection based on several factors including but not limited to the internship availability and business needs of this role. About the team The Personal Robotics Group is pioneering intelligent robotic products that deliver meaningful customer experiences. We're the team behind Amazon Astro, and we're building the next generation of robotic systems that will redefine how customers interact with technology. Our work spans the full spectrum from advanced hardware design to sophisticated software and control systems, combining mechanical innovation, software engineering, dynamic systems modeling, and intelligent algorithms to create robots that are not just functional, but delightful. This is a unique opportunity to shape the future of personal robotics working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. Join us if you're passionate about creating the future of personal robotics, solving complex challenges at the intersection of hardware and software, and seeing your innovations deliver transformative customer experiences.

Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for an Applied Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market. Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects. As an Applied Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership. Key job responsibilities - Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network. - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics. - Develop end-to-end solutions, tools and frameworks to scale our ML model development and data analysis. - Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features. - Present research findings and recommendations to scientists, business leaders, and executives. - Collaborate with cross-functional teams to drive adoption of models and insights. - Stay current on latest developments in relevant fields and propose innovative approaches. About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.

Amazon Web Services (AWS) is assembling an elite team of world-class scientists and engineers to pioneer the next generation of AI-driven development tools. Join the Amazon Kiro LLM-Training team and help create groundbreaking generative AI technologies including Kiro IDE and Amazon Q Developer that are transforming the software development landscape. Key job responsibilities As a key member of our team, you'll be at the forefront of innovation, where cutting-edge research meets real-world application: - Push the boundaries of reinforcement learning and post-training methodologies for large language models specialized in code intelligence - Invent and implement state-of-the-art machine learning solutions that operate at unprecedented Amazon scale - Deploy revolutionary products that directly impact the daily workflows of millions of developers worldwide - Break new ground in AI and machine learning, challenging what's possible in intelligent code assistance - Publish and present your pioneering work at premier ML and NLP conferences (NeurIPS, ICML, ICLR , ACL, EMNLP) - Accelerate innovation by working directly with customers to rapidly transition research breakthroughs into production systems About the team The AWS Developer Agents and Experiences (DAE) team is reimagining the builder experience through generative AI and foundation models. We're leveraging the latest advances in AI to transform how engineers work from IDE environments to web-based tools and services, empowering developers to tackle projects of any scale with unprecedented efficiency. Broadly, AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. 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 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner. We are looking for an enthusiastic, customer obsessed, Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Operations Research Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon. Candidates will be a high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of operations research, and the ability to use data and research to make changes. This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Responsibilities may include: - Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations - Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans - Managing multiple projects simultaneously - Working with technology teams and product managers to develop new tools and systems to support the growth of the business - Communicating with and supporting various internal stakeholders and external audiences

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! We are seeking a Data Scientist to help drive Prime Air’s expansion through applied ML and rigorous experimentation. You’ll work with engineers, analysts, and domain partners to translate customer journey and behavioral data (e.g., clickstream signals) into predictive models, causal insights, and measurable interventions identifying high-opportunity segments, diagnosing adoption friction, and improving reach and conversion. If you enjoy building models that ship, designing experiments that change decisions, and operating end-to-end from data to impact, we’d love to hear from you. Key job responsibilities Key responsibilities include: - Developing new statistical, causal, and machine learning techniques and develop solution prototypes to drive innovation - Collaborate cross-functionally to deeply understand business requirements, customer needs, and technical constraints - Drive the research, design, and development of novel ML/AI models and systems to power critical products and services - Present insights, recommendations, and results to senior leadership through written reports and verbal presentations, earning trust through clear articulation of data-driven findings and their business impact. - Stay up-to-date on the latest advancements in AI/ML and identify opportunities to apply emerging techniques

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and fine-tuning LLMs? 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 and fine-tuning 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. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, execute experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the organization. You get to influence stakeholders with clear communication skills. You innovate on behalf of the customer and strategically build features. You will mentor junior members and help them grow. About the team The team values innovations and offers a safe place to try, fail and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. Our team offers creative space with entrepreneurial work environment focusing on customer obsession.

The Amazon Search team creates customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers, countries, categories, and product lines. We are seeking a strong applied scientists to join the newly formed Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models. Key job responsibilities Build machine learning models for Product Search. Develop new ranking features and techniques building upon the latest results from the academic research community. Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system. Focus on identifying and solving customer problems with simple and elegant solutions. Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment. Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems. Take ownership. Understand the needs of various search teams, distil those into coherent projects, and implement them with an eye on long-term impact. Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects. Be ambitious. Find and eagerly tackle hard problems. Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively. Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.

Amazon’s Customer Behavior Analytics org is looking for an Senior Manager, Applied Science, to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable ML and causal inference solutions to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. This is a high-impact role with opportunities to develop systems that affect investments to the size of billions of dollars. We work closely with business stakeholders and strive to continuously produce tangible impact on the company’s strategic and tactical planning and operations. A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate complex business problems into scientific challenge, and deliver data driven solutions - which will allow Amazon to make key investment decisions.You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine/deep learning at scale. You should have strong analytical and communication skills, be able to work with stakeholders and partners which include world-wide business leaders, distinguished scientist, economist, product managers and software teams. You will apply your expertise in Economics, ML/DL, statistics, and data-wrangling to identify opportunities for further research and to provide insights that drive larger initiatives. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization. Key job responsibilities The main responsibilities for this position include: - Apply your expertise in ML/DL and statistical modeling to develop solutions and systems that describe how Amazon’s marketing campaigns impact customers’ actions - Own the end-to-end development of novel causal inference models that address the most pressing needs of our business stakeholders and help guide their future actions - Recruit high performing Economist, Applied Scientists and BIEs to the team and provide mentorship. - Establish team mechanisms, including team building, planning, and document reviews. - Review and audit modeling processes and results from scientists within and outside your team - Work with marketing leadership to align our measurement plan with business strategy - Formalize assumptions about how our models are expected to behave and explain why they are reasonable - Identify new opportunities that are suggested by the data insights - Bring a department-wide perspective into decision making About the team The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.