Careers

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.

Amazon Selling Partner Services (SPS) team's mission is to make Amazon the safest and most trusted place worldwide to transact online. Amazon runs one of the most dynamic e-commerce marketplaces in the world, with nearly 2 million sellers worldwide selling hundreds of millions of items in ten countries. SPS safeguards every financial transaction across all Amazon sites. As such, SPS designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon.com. SPS organization is looking for a Data Scientist for its Forecasting and Planning Research team. The team is being grown to provide insights about its SPS planning and provide analytical solutions to help drive operational efficiencies, uncover the hidden risks and trends, reduce investigation errors and bad debt, improve customer experience and predict & recommend the optimizations for future state of SPS operations. As a Data Scientist, you will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques, with a strong emphasis on leveraging Generative AI and Large Language Models (LLMs) to drive innovation. You will develop and deploy Gen AI-powered solutions for intelligent forecasting, automated pattern recognition in variance analysis, and conversational AI interfaces for operational dashboards. The role requires building agentic AI systems that enable natural language querying, automated root cause analysis, and intelligent recommendation engines for workforce optimization and resource planning. You will need to collaborate effectively with internal stakeholders and cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidate should be able to apply a breadth of tools, data sources and analytical techniques—including transformer architectures, foundation models, and prompt engineering—to answer a wide range of high-impact business questions and present the insights in concise and effective manner. Additionally, the candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business.

What happens when you combine startup speed with Amazon-scale impact? You get this team. Amazon Enterprise Security Products is a newly launched group building intelligent, cloud-agnostic security tools using AI-first development practices. Here, you build AI and you build with AI — at the same time. This role is a chance to shape the future of security tooling with a small, fast team that ships like a startup but deploys at Amazon scale. We're looking for a Data Scientist who thrives at the intersection of applied ML, agentic AI, and security. You'll design and deploy models that detect threats, power intelligent agents, and make security decisions at cloud scale. You'll work shoulder-to-shoulder with SDEs, applied scientists, security researchers, and PMs on a team where the best idea wins, regardless of title or tenure. Key job responsibilities * Build the intelligence behind AI-first security products: Design, train, and ship ML models that power agentic systems, anomaly detection, threat classification, and automated response — all running across multi-cloud environments. * Own the full science lifecycle: From problem framing and data exploration through model development, evaluation, production deployment, and monitoring. You build it, you ship it, you run it. * Build with AI to build AI: Use agentic coding tools, LLM-powered workflows, and experimental AI tooling to accelerate every phase of your work; from EDA to feature engineering to model iteration. Multiply your velocity and raise the bar for what one scientist can deliver. * Power agentic architectures: Develop the models, embeddings, RAG pipelines, evaluation frameworks, and feedback loops that make multi-agent security systems smart, safe, and customer-ready. * Prototype rapidly and validate with customers: Turn hypotheses into prototypes in days, not quarters. Iterate based on real customer signal and ship what works. * Partner across disciplines: Work directly with SDEs, applied scientists, security researchers, PMs, and UX designers to turn ambiguous problems into shipped solutions. Small team means short lines between you and the decision. * Communicate with impact: Translate complex modeling results into clear recommendations for engineers, product leaders, and senior executives. Influence direction with data. * Raise the science bar: Contribute to technical and science reviews, mentor teammates, and champion AI-first development practices. Help shape the science culture of a fast-growing team from the ground floor. A day in the life No two days look the same on this fast-growing, AI-first team. You might start your morning reviewing evaluation results from overnight model training runs, then dive into building a RAG pipeline or tuning a multi-agent orchestration loop. Before lunch, you're pair-prompting with an agentic coding assistant to stand up a new feature pipeline. In the afternoon, you join a design session with senior and principal scientists and engineers where your ideas carry weight regardless of title. You own science problems end to end, ship using the latest AI-assisted workflows, and see your models reach production fast. This is where builders thrive. About the team Amazon Enterprise Security Products is built by builders who tackle challenges others might consider too ambitious. We're a small team where there are no layers between you and the decision, no waiting quarters to see your work reach customers. Every team member brings an owner's mentality. If there's a problem worth solving, we solve it. No mission is beyond reach, no detail beneath our attention. We move fast, we ship fast, and we learn from what we ship. This is where builders who want to make the impossible routine come to do their best work. Diverse Experiences Amazon Security 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 Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

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!

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.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Key job responsibilities - Develop AI solutions for various Prime Video Search systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON DEVELOPMENT CENTER U.S., INC. Offered Position: Applied Scientist III Job Location: Boston, Massachusetts Job Number: AMZ9898584 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. 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 $167,100/year to $226,100/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: Data Scientist III Job Location: North Reading, Massachusetts Job Number: AMZ9898176 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy. Position Requirements: Master's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization. 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 $161,803/year to $215,300/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

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.