Careers

Are you passionate to join an innovative team of scientists and engineers who use machine learning and AI techniques to create state-of-the-art solutions to help seller succeed on Amazon? The Selling Partner Selection Success org is looking for a Principal Applied Scientist to lead us on our mission to provide selection success support on Amazon, and empower sellers to grow their business and provide a great customer experience. As a Principal Applied Scientist on our team of scientists and engineers, you will have opportunities to create significant impact on our systems, our business and most importantly, our customers as we take on challenges that can revolutionize the e-commerce industry. You will identify specific and actionable opportunities to solve business problems, propose state-of-the-art solutions and collaborate with engineering, and business teams for future innovation. You need to be a great translation between ambiguous business domains and rigorous scientific solutions, an expert at inventing and simplify, and a good communicator to surface insights and recommendations to audiences of varying levels of technical sophistication. Key job responsibilities - Drive and advocate technical vision that drives the significant business impact - Use machine learning and AI techniques to create scalable seller-facing solutions - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, development and evaluation of highly innovative models - Work closely with software engineering teams to drive real-time model implementations and new feature creations

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2026, we are focused on economics and science in areas related to (1) lowering cost-to-serve, (2) optimizing selection, and (3) emerging machine learning. We also have some ongoing and highly-leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for an Applied Scientist to build and deliver state-of-the-art science and engineering solutions to improve our Stores business. In this role, you will work in a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing and maintaining the scientific models, benchmarks, and services. Graduate education or hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a big plus. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity. Key job responsibilities The successful candidate will lead large-scale science initiatives from research to production and translate complex business problems into mathematical frameworks. They will design and implement large-scale algorithms for complex supply chain and marketplace problems, and design incentive-compatible mechanisms for marketplace challenges. The ideal candidate will have a strong publication record in top-tier conferences/journals (INFORMS, EC, WINE, ICML, NeurIPS, etc.) and experience coordinating cross-functional projects. Hands-on experience building science solutions to mechanism design problems (e.g., optimal auction design, welfare maximization under constraints, incentive compatible coordination), with expertise in statistical learning and algorithm development. Leadership responsibilities include influencing technical strategy and roadmaps for complex initiatives, influencing senior stakeholders and shaping technical direction, and fostering team growth.

We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies, and experimentation to drive product decisions and optimize customer experiences. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems. Key job responsibilities Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems. A day in the life Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations. About the team The Alexa for Shopping Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the AfS AI, from making it agentic, enabling customers to set price alerts or empower AfS to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.

AWS Security is seeking a Research Scientist to apply rigorous quantitative methods to problems at the intersection of cloud security and customer experience. In this role, you will design and conduct large-scale research studies—leveraging advanced statistical modeling, survey research, and behavioral science—to surface actionable insights. Key job responsibilities Design and develop quantitative measurement models—including structural equation models (SEM) and latent variable frameworks—that map the relationships between security experiences and customer perception outcomes. Define and validate customer perception constructs through confirmatory factor analysis, survey design, and large-scale data collection across diverse customer segments, including technical and non-technical decision-makers. Extend existing scientific techniques and invent new approaches to address complex measurement challenges in the enterprise and emerging technology domain, including multi-stakeholder modeling, cross-segment analysis, and longitudinal study design. Partner cross-functionally with security specialists, program managers, and customer teams to integrate data sources into a unified research program. Establish baseline metrics and develop leading and lagging indicators that enable data-driven goal-setting and ongoing measurement of customer perception trends over time. Ensure scientific rigor by documenting methodology, validating model fit using established statistical criteria, and maintaining reproducibility of results. A day in the life You will spend your time designing research instruments, analyzing complex multi-source datasets, iterating on quantitative models, and presenting findings to senior leaders. You will collaborate with program managers, engineers, and strategists to connect research insights to real-world customer outcomes. About the team The AWS Security team owns security for all services offered by AWS, including EC2 and S3. This creates a lot of different opportunities for cross-team collaboration and high visibility into the company. We dive deep into security technologies to innovate and provide our customers the best possible experience with every transaction that happens in the cloud. As part of the AWS Security team, you’ll work alongside a motivated and diverse team eager to transform the cloud security landscape. 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.

The AI Center of Excellence (AICE) builds AI primitives that power system-intrinsic intelligence and Trusted Intelligent Knowledge Infrastructure for both AI-as-a-Consumer and human users. We develop AI capabilities independently and in partnership with product-owning teams to evolve Amazon's AI-driven operations and productivity. Our impact is enterprise-broad and global. We are looking for an Applied Scientist who can identify high-impact problems, design rigorous experiments, and translate research into hardened, reusable primitives ready for broad consumption across the enterprise. Key job responsibilities * Research, design, and develop AI/ML primitives - defining problem spaces, formulating approaches, running experiments, and validating outcomes with scientific rigor * Translate research findings into production-ready primitives, working closely with machine learning engineers to harden and scale solutions * Drive the scientific direction of AICE primitives, identifying opportunities where novel approaches can unlock step-function improvements * Design and execute experiments to validate primitive performance, robustness, and generalizability before broad consumption by partner teams * Collaborate with product-owning teams to understand their problem spaces and ensure AICE primitives deliver measurable value when integrated * Contribute to AICE's mission of driving AI transformation through best practices in applied research, evaluation methodology, and responsible AI within your area of expertise * Publish findings, share learnings, and raise the scientific bar across the team A day in the life Every day brings new challenges. You might be deep in experimentation - designing evaluations to stress-test a new primitive's robustness. The next day, you could be analyzing results and iterating on model architectures. Later in the week, you may collaborate with partners to understand their domain and shape a primitive that fits their product needs. Other days, you'll work alongside our MLEs to harden a validated approach for broader consumption. No two weeks look the same. You'll move fluidly between research and applied problem-solving - always with the goal of building AI primitives that are scientifically sound, trusted, and impactful at enterprise scale. About the team AICE is a team of scientists and machine learning engineers building the AI primitives that power Amazon's intelligent systems. We develop and harden reusable capabilities for broad consumption by product teams across the enterprise - and partner with those teams to integrate them.

We are seeking an Economist to join our growing team in Japan. In this role, you will apply rigorous economic and econometric methods to guide critical business decisions affecting Amazon's JP marketplace. You will build causal inference models to measure the impact of business initiatives on pricing, product selection, delivery speed, profitability, and customer experience. Working alongside economists, data scientists, and business intelligence engineers, you will tackle challenging problems using state-of-the-art analytical techniques while providing advisory support to business stakeholders. As one of the first economists based outside North America and EU, you will play a pioneering role in expanding Amazon's economist community in Asia and make an outsized impact on our international marketplace operations. Key job responsibilities Design and execute causal inference analyses using econometric techniques to measure the impact of business initiatives on key marketplace metrics Build economic models to optimize pricing strategies, product selection decisions, and delivery speed investments that balance customer experience with business profitability Collaborate with product managers, engineers, and business leaders to translate complex business questions into tractable research problems and deliver actionable insights Design and analyze experiments to test hypotheses and validate causal relationships in observational data Develop scalable analytical frameworks and tools using R, Python, or Stata that can be leveraged across multiple business use cases Present findings and recommendations to technical and non-technical audiences, including senior leadership, through clear written narratives and data visualizations Partner with Machine Learning and BI team members to integrate economic insights into automated decision-making systems About the team The JP Economics and Decision Sciences team is a central science team that applies rigorous economic theory, causal inference methods, and machine learning to solve complex business challenges across the JP marketplace and beyond. We work closely with JP business leaders to drive change at Amazon, focusing on solving long-term, ambiguous problems while providing advisory support for short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel economic and econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with JP-, EU-, and US-based interdisciplinary teams.

The Data Intelligence team is a new function within Amazon Customer Service. We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data strategy. We also develop and apply Generative Artificial Intelligence (GenAI), Machine Learning (ML), Ontology, and Natural Language Processing (NLP) to enhance customer service associate and customer experiences. As an Applied Scientist, you'll own the definition and implementation of customer-focused, AI-driven innovation in Amazon Customer Service globally, leveraging GenAI, ML, and/or NLP to transform complex business requirements and customer needs into innovative technology solutions. Your expertise will be key in shaping data-driven strategies and addressing complex data challenges. With your expertise in AI, text analysis, embeddings, language modeling, and generation, you'll design and develop scalable AI-powered technology solutions, prioritize initiatives, drive data-driven insights, and deliver business impact. This position will advance applied science best practices, leverage data and AI to drive customer experience improvements, and set new global standards for customer experience. This role requires you to work with a cross-functional team, including scientists, engineers, and product managers, to develop scalable and maintainable AI solutions for both structured and unstructured data. The ideal candidate has strong technical skills in AI techniques (e.g., automated reasoning, reasoning, planning, knowledge representation), excellent written documentation skills, and experience with big data technologies. Success in this role requires combining deep business knowledge with hands-on technical skills to solve customer problems and address complex technical challenges. Key job responsibilities - Develop innovative solutions to complex problems (e.g., Automated Reasoning for Trusted AI-Enabled Customer Service). - Apply technical expertise to implement novel algorithms and modeling solutions, in collaboration with other scientists and engineers. - Analyze data and define metrics to identify actionable insights and measure improvements in customer experience. - Communicate results and insights to both technical and non-technical audiences through written reports, presentations, and internal/external publications. - Collaborate with product management and engineering teams to integrate and optimize models in production systems. A day in the life A typical day as an Applied Scientist in the Data Intelligence team involves combining business expertise with hands-on problem-solving in ML and AI. The role encompasses tackling complex data initiatives, ensuring alignment with customer needs and business objectives, and translating business requirements into practical AI-driven solutions. Working collaboratively with cross-functional teams, this position involves designing and enhancing AI models, focusing on efficiency, precision, and scalability. Daily activities include ensuring data quality, monitoring model performance, and generating actionable insights from vast amounts of information. Each day presents opportunities to resolve complex technical challenges, advance important AI projects, and conceive innovative ways to leverage data in transforming the customer experience. About the team The Data Intelligence team is a new function within Amazon Customer Service. We develop and apply Generative Artificial Intelligence (GenAI), Machine Learning (ML), Ontology, and Natural Language Processing (NLP) to enhance customer service associate and customer experiences.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers and enhance the shopping experience, for customers. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities We are looking for an Applied Scientist to join the Sponsored Prompts team within the Conversational Discovery Experiences (CAX) in Sponsored Products and Brands. This team owns Sponsored Prompt generation, quality and personalization, a new conversational ad format powered by large language models (LLMs) that helps shoppers discover products across Amazon.com. As an Applied Scientist, you will design and build core components of the prompt generation pipeline, develop new prompt themes, and improve quality frameworks that drive coverage expansion across all surfaces. You will define and run experiments to improve CTR, helpfulness, and advertiser outcomes, and contribute to the science roadmap for prompt generation and personalization. This role requires strong technical depth in NLP, LLMs, and information retrieval, combined with the ability to translate research into production systems at scale. You will work across organizational boundaries with engineering, product, and business teams to turn science investments into measurable business impact.

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities Participate in the Science hiring process as well as mentor other scientists - improving their skills, their knowledge of your solutions, and their ability to get things done. Identify and devise new video related solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level. Articulate potential scientific challenges of ongoing or future customers’ needs or business problems, and present interventions to address them. Independently assess alternative video related technologies, driving evaluation and adoption of those that fit best A day in the life As an Applied Scientist on the Sponsored Brands Video team, you will work with a team of talented and experienced engineers, scientists, and designers to help bring new products to market and ensure that our customers are delighted by what we create. The Sponsored Brands Video team is responsible for the design, development, and implementation of Sponsored Brands Video experiences worldwide. About the team The Sponsored Brands Video team within Sponsored Products and Brands creates relevant and engaging video experiences, connecting advertisers and shoppers. We are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping delightful, & personal.

Amazon Ads is a multi-billion dollar global business that delivers advertising experiences across Amazon's owned-and-operated properties (including Prime Video, Twitch, Fire TV, and Amazon.com), third-party publisher networks, and emerging channels like generative AI-powered shopping experiences. As one of the fastest-growing segments of Amazon, we operate at unprecedented scale across desktop, mobile, connected TV, and emerging surfaces. Within Amazon Ads, Traffic Quality is a critical pillar of advertiser trust and marketplace integrity. Our mission is to build advanced capabilities that work at petabyte scale to detect sophisticated invalid traffic (IVT) which includes sophisticated non-human traffic, bot networks, and fraudulent engagement patterns across programmatic advertising. We are on a journey to establish Amazon Ads as an industry leader in traffic quality standards and transparency. Our research agenda focuses on staying ahead of adversarial actors through continuous innovation in detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall while operating under strict latency constraints. Our work directly protects hundreds of millions of dollars in advertiser spend annually while maintaining a seamless user experience. Key job responsibilities As a Data Scientist II in Traffic Quality, you will solve inherently hard problems in advertising fraud detection by applying advanced statistical techniques and machine learning. You'll work on systems that process billions of ad impressions and clicks per day, using Amazon's cloud services including EC2, S3, EMR, Sagemaker, and RedShift. - Define and frame new research problems in fraud detection where neither problem nor solution is well-defined. - Apply new machine learning approaches, models, and algorithms to detect sophisticated invalid traffic. - Apply domain knowledge to perform broad data analysis as a precursor to modeling and build business insights. - Work with unstructured and massive datasets to deliver results. - Produce research reports meeting top-tier external publication standards. - Mentor and develop junior scientists on the team. About the team Here are a few papers published by the team: 1/ [Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD 2023.](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) 2/ [SLIDR: Real-time Robot Detection On Online Ads, IAAI 2023, Deployed Highly Innovative Applications of AI Track (AAAI 2023)](https://assets.amazon.science/75/2f/3b7106b143f38f7f4d2806388ace/real-time-detection-of-robotic-traffic-in-online-advertising.pdf) 3/ [Self-supervised Representation Learning Across Sequential and Tabular Features Using Transformers, NeurIPS 2022, First Table Representation Learning Workshop](https://openreview.net/forum?id=wIIJlmr1Dsk)