Careers

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, Sr. 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. Ideal 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

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 Research 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 a Research 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.

Interested in influencing what customers around the world see when they turn on Prime Video? The Prime Video Personalization and Discovery team matches customers with the right content at the right time, at all touch points throughout the content discovery journey. We are looking for a customer-focused, solutions-oriented Principal Data Scientist to develop next-gen measurement and experimentation systems within Prime Video Personalization and Discovery. You'll be part of an embedded science team driving projects across product and engineering teams that ultimately influence what millions of customers around the world see when the log into Prime Video. The ideal candidate brings experience building experiment-based measurement systems at scale, excellent stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video for high-quality, rigorous measurement, assess business problems, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Define and drive the multi-year vision for experiment-based measurement systems within Prime Video - Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience - Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Mentor junior scientists and review technical artifacts to ensure quality - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization

The Customer Behavior Analytics team designs innovative machine learning solutions to enhance customer experiences and strengthen their relationship with Amazon. This interdisciplinary team of scientists and engineers incubates and develops disruptive solutions using state-of-the-art technology to tackle some of the most challenging scientific problems in customer behavior analysis at Amazon. To achieve this, the team utilizes methods from deep learning, large language models (LLMs), natural language models, recommendation systems, affinity models, reinforcement learning, and econometrics to drive personalized experiences throughout the customer journey. As a Customer Behavior Analytics Scientist, you will have the opportunity to make a significant business impact, delve into large-scale problems, drive measurable actions, and collaborate closely with other scientists and engineers. You will be responsible for designing and developing state-of-the-art models and working with business, marketing, and engineering teams to address key challenges in customer behavior analytics. Key responsibilities include: - Design and fine-tune language and generative models for recommendation and engagement, including continued pre-training, supervised fine-tuning, and preference-based alignment, to optimize for long-term customer value rather than short-term clicks. - Develop generative recommendation and decision models that produce next-best customer engagement actions (e.g., recommendations, bundles, messaging, incentives, timing), conditioned on structured customer and household-level behavioral context. - Build structured, temporal representations of customer behavior (e.g., lifecycle stage, needs, replenishment patterns, engagement history) and integrate them into generative and deep learning models to enable long-horizon reasoning. - Experiment scalable representations of customer and household behavior that summarize long engagement history into compact states, supporting efficient, incremental inference in large-scale inference. - Design and apply post-training optimization techniques (e.g., auxiliary objectives, preference modeling, offline reinforcement learning or policy optimization) to align model behavior with long-term engagement, satisfaction, and retention metrics. - Develop robust evaluation frameworks combining offline metrics, counterfactual analysis, and online experimentation to measure both immediate impact and long-term customer outcomes. In this role, you will be an analytical problem solver who enjoys exploring data, participating in problem-solving efforts, developing new frameworks, and engaging in investigations and algorithm development. You should be capable of effectively collaborating with technical teams and business stakeholders, pushing the boundaries of what is scientifically possible, and maintaining a sharp focus on measurable customer satisfaction and business impact. Your work will be crucial in shaping the future of customer behavior analytics at Amazon, driving innovation that directly impacts millions of customers worldwide. This position offers a high-visibility opportunity to contribute to solutions that are vital to improving customer satisfaction and loyalty, serving as a model for customer-centric solutions across the company.

Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot We are the Optimal Sourcing Systems team (OSS) within SCOT and are looking for a Data Scientist II to join us! OSS designs and builds systems that measure and manage Amazon’s supplier capabilities, identify and react to supply disruptions, and prioritizes inbound freight for our global network. OSS software is used by every country Amazon services, and is a critical link to ensuring Amazon offers the products our customers want, at the lowest possible cost. This team under OSS orchestrates and tracks inventory movement into Amazon's network, maintains performance feedback loops, and ensures vendor compliance. The Data Scientist II, in partnership with the Product Management, Operations, and Tech teams, will lead efforts in four areas: 1) Building models to set optimal parameters such as lead times to ensure the accuracy of our Inbound network 2) Building analytical frameworks to identify and drive improvements in purchase order lifecycle management and defect coaching/chargebacks 3) Developing Gen AI solutions related to dispute evaluation and vendor coaching 4) Building models and solutions to enable collaborative inventory planning with vendors The ideal candidate thrives in ambiguous problem spaces, relishes working with large volumes of data, and enjoys the challenge of highly complex supply chain contexts. They can translate complex business logic into scalable models and communicate insights effectively to both technical and non-technical stakeholders. Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. Experience with supply chain optimization, operations research, or vendor management systems is a plus. Key job responsibilities - Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems - 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 - Drive technical standards and best practices for the team's Science solutions - Mentor and provide technical guidance to other team members on complex projects A day in the life 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!

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Amazon ‘s Tax engine organisation is looking for a passionate and innovative science leader to take its science initiatives to new heights. Amazon Tax Engine platform backs all of the orders placed across Amazon e-commerce. We serve Amazon customers and sellers by correctly computing and collecting the tax amounts when an Amazon order is placed globally. We are responsible for correctly attributing products to the correct Tax categories applicable for the specific country, state and county, providing core calculation services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, with accuracy close to 100%. We use language models at scale for Tax classification of the diverse products in Amazon catalogue We have a growing portfolio of science problems that includes balance of predictive and generative AI -including language comprehension, causal reasoning and active learning. Key job responsibilities - Manage and mentor a talented team of senior Appleid Scientists and SDEs. - Improve process and methodologies pertaining to deliverables of the team. - Strike the right balance between experimentation and delivery for sustained impact and long term gains. - Partner with stakeholders and customers to build roadmap for new products and services.

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 foundation models for content understanding using state-of-the-art deep learning and multimodal learning techniques to analyze video, audio, and text. Build time sequence foundation models to understand and predict customer behavior patterns and viewing trajectories. Work closely with engineers and product managers to design, implement and launch solutions end-to-end across various Prime Video experiences. 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 foundation models, multimodal learning, and time series analysis. Publish your research findings in top conferences and journals. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.

Are you passionate about Generative AI? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help our customers build and deploy GenAI enabled applications using Amazon Bedrock, customize Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. We work backwards from our customer’s most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam The Generative AI Worldwide Specialist team guides AWS customers on building enterprise-grade GenAI systems. This role will support development of techniques, solutions and architectural blueprints that our customers can use to build their own enterprise-wide Generative AI and Agentic systems in a responsible way, helping them balance democratization of access to GenAI and speed of innovation with following best practices around trustworthy AI, cost efficiency, security, etc. This role specifically will be owning development of best practices around Responsible AI covering such important topics as guardrails, veracity, model evaluations, automated reasoning, fairness, explainability, etc. The role with partner with others on the team to develop comprehensive guidance for AWS GenAI customers using Amazon Bedrock. The deliverables include: helping customers solve complex problems with data science, contributions to the joint technical guidance, architectural blueprints / whitepapers, feedback to AWS Bedrock science teams, thought leadership in the form of public writing and speaking, as well as internal enablement. The role has a global remit. Key job responsibilities - Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, troubleshoot customer issues, and explore new solutions. You will interact closely with our customers and with the academic community. - Thought Leadership – Evangelize AWS features relating to Responsible AI and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements. - Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.