Careers

As a Data Scientist on our team, you will leverage advanced analytics and machine learning to protect our cloud infrastructure from security threats. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify and automate the mitigation of cyber threats across Amazon's infrastructure. Your expertise in statistical analysis, machine learning, and big data processing will be crucial in building scalable security solutions. You'll collaborate with software engineers, security engineers, and fellow data scientists to: - Analyze large-scale security data using statistical methods and data mining techniques - Create automated systems for real-time pattern recognition and risk assessment - Build data pipelines and ETL processes to handle massive security datasets - Translate complex analytical findings into actionable security insights We use the full power of AWS technologies, including Amazon SageMaker, EMR, and other ML/AI services to protect every AWS customer from security threats. Experience with Python and a strong background in statistical analysis and machine learning are essential. We're looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we've been building. We understand that life is dynamic and we have a flexible work environment that enables individuals to adjust their work schedule to accommodate personal needs. Our team is distributed, though most of the team is located in Maryland and Virginia. We generally keep core business hours of 10:00 AM EST - 3:00 PM EST, while allowing flexibility as needed. At AWS Security, it’s not about clocking hours, it’s about delivering results. On-Call Responsibility This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice. Key job responsibilities - Running experiments to assess potential risk of security responses. - Expanding our existing LLM agent pipelines - Analyzing post mortems to understand what data signals could have prevented the occurence About the team 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.

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! Key job responsibilities Develop foundation models for content understanding using state-of-the-art deep learning and multimodal learning techniques to analyze video 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 A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. 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.

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.

Amazon is investing heavily in building a world-class advertising business, and we are responsible for defining and delivering a collection of advertising tools and products that drive discovery and Advertiser success. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action. The Marketing Effectiveness & Attribution Science team develops causal inference and machine learning systems to measure the impact of marketing programs across Amazon's advertising ecosystem. We build production-grade attribution models that help business teams understand what's working, optimize resource allocation, and drive advertiser growth. Our work sits at the intersection of econometrics, scalable ML systems, and high-stakes business decisions. As a Data Scientist on this team, you will own end-to-end modeling pipelines — from problem formulation and experimental design to model development, productionization, and stakeholder communication. Major responsibilities include: Translate / Interpret: Partner with cross-functional teams to translate business questions into rigorous causal inference problems Design observational studies and quasi-experiments to measure marketing effectiveness when traditional A/B tests are infeasible Work with data engineering to instrument new data pipelines when existing data cannot answer the causal question Measure / Quantify / Expand: Own and evolve production attribution models across multiple marketing channels Build and maintain causal inference pipelines using methods such as Difference-in-Differences, Synthetic Control, Double Machine Learning, and Media Mix Models Develop scalable PySpark and Python codebases that process large-scale event data Continuously improve model accuracy through feature engineering, heterogeneity analysis, and sensitivity testing Explore / Enlighten: Investigate anomalies in model outputs and deep-dive to identify root causes Develop automated data quality checks and model diagnostics Research and prototype next-generation measurement methods Make Decisions / Recommendations: Present findings to senior leadership with clear recommendations Build dashboards and self-service tools that enable stakeholders to explore results independently Write production-quality Python code for data analysis, model training, and result publishing

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Our products are used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. We are looking for an experienced Economist with a deep passion for building econometric solutions and the ability to communicate data insights and scientific vision to execute on strategic projects. Key job responsibilities - Leverage econometrics and ML models to optimize advertising strategies on behalf of our customers. - Influence key business and product decisions based on insights from models you develop. - Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience. - Work closely with software engineers on detailed requirements to productionize the models you build. - Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Work with other scientists, software developers, and product partners to implement your solutions.

The newest business group in AWS, Applied AI Solutions are built by AWS and AWS Partners to deliver applied AI solutions that leverage Amazon's operational expertise and that businesses love and trust for their day-to-day success. Our ambition is to become a partner which companies can rely on to run their business every day, putting AI to work delivering better customer experience, operational excellence and speed. Are you excited about pushing past single-turn chat into agents that run for hours or days, planning, recovering from failure, and accumulating knowledge as they work? Do you want to design the harnesses, memory systems, and context strategies that turn frontier models into reliablen collaborators on real business problems? Do you enjoy the prospect of solving agent problems that haven't been solved at scale anywhere before, including memory decay, belief revision, fact grounding, long-horizon credit assignment, and evaluation of open-ended trajectories? Along the way, you'll get opportunities to be a disruptor, innovator, and a problem solver, someone who truly enables AI agents to create significant impacts. Key job responsibilities You will partner with cross-functional business and engineering teams to identify and deliver high-impact agentic use cases across the Applied AI Solutions portfolio. You will design, develop, and evaluate long-running agents — including orchestration harnesses, memory architectures (episodic recall, semantic facts, revisable beliefs, principled decay), context compaction strategies, and safe, auditable tool and environment designs. You will define evaluation frameworks for agents whose outputs defy single-answer judgment, building trajectory-level evaluations, reward-hacking detection, and human-in-the-loop review patterns. As a senior scientist, you will set technical direction, mentor scientists and engineers, and represent the science org in roadmap and architecture decisions. You will ensure seamless deployment and integration of agents into production systems customers rely on daily. The ideal candidate thrives in ambiguity, builds collaborative relationships, moves fast, and is passionate about customer experience. They hold a strong point of view on where agent capabilities are heading, with the scientific rigor to separate what works from what merely demos well. They lead by example, communicate effectively across audiences, and love solving complex problems at the frontier of applied AI.

The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. PXTCS is looking for an economist who can apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure impact, and transform successful prototypes into improved policies and programs at scale. PXTCS is looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities - Design and conduct rigorous evaluations of benefits programs - Support the development and application of structural models - Develop experiments to evaluate the impact of benefits initiatives - Communicate complex findings to business stakeholders in clear, actionable terms - Work with engineering teams to develop scalable tools that automate and streamline evaluation processes A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team PXTCS is a multidisciplinary science team that develops innovative solutions to make Amazon Earth's Best Employer

The AWS Marketplace team is looking for an Applied Scientist to help build and improve our AI/ML-Powered Discovery systems. The ideal candidate is passionate about applying machine learning and artificial intelligence to complex information retrieval challenges, with experience in search, recommendations, or personalization. You'll work alongside senior scientists and engineers to develop models and systems that power traditional discovery experiences — such as search ranking, query understanding, and personalized recommendations — built on rich product knowledge graphs and structured metadata. You'll also help extend these foundations into emerging agentic discovery experiences, where AI agents leverage these retrieval and knowledge systems to help customers find and evaluate software solutions. This is a great opportunity to have direct impact on the future of software discovery on AWS Marketplace. Key job responsibilities - Design, develop, and deploy AI/ML models for search ranking, query understanding, recommendation, and discovery systems - Develop and improve information retrieval systems that operate over complex product taxonomies, knowledge graphs, and structured/unstructured metadata - Build relevance models that capture nuanced relationships between customer intent, product capabilities, and domain-specific context - Advance both traditional discovery experiences (search, browse, personalized recommendations) and agentic discovery with multi-agent systems - Conduct experiments and A/B tests to measure and improve the relevance and performance of discovery features - Analyze large-scale datasets to identify patterns, generate insights, and inform model development - Collaborate with engineers and product managers to integrate AI/ML solutions into production systems - Stay current with relevant research in information retrieval, knowledge representation, NLP, and recommendation systems, and apply findings to improve our systems About the team The AWS Marketplace & Partner Services Science team is at the forefront of developing and deploying AI/ML systems that serve multiple critical stakeholders: - AWS Customers: Through the AWS Marketplace, we support Discovery tools that streamline cloud adoption and innovation. - AWS Partners: Via Partner Central, we offer advanced tools and insights to enhance collaboration and drive mutual growth. - Internal AWS Sellers: We equip our sales force with data-driven recommendations to better serve our customers and partners. Our primary objective is to accelerate cloud migrations and modernizations, fostering innovation for AWS customers while simultaneously supporting the growth and success of our extensive partner network. 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. 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. Mentorship and 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. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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.

We are seeking an exceptional Senior Data Scientist to join our JP Seller Services team, where you will play a pivotal role in enabling seller growth and success on Amazon Marketplace through innovative products, technology, and data-driven solutions. As a key member of JP Seller Services, you will collaborate with cross-functional stakeholders across Amazon to develop sophisticated AI-native science solutions and innovative problem-solving products through advanced analytics, machine learning, statistical modeling and generative AI. These solutions will enable seller business growth on Amazon Marketplace and deliver key strategic decisions impacting our entire business. The ideal candidate combines strong technical depth with the strategic thinking to address complex business problems at scale. Key job responsibilities (1) Implement AI-driven solutions to streamline and accelerate the science model development and evaluation cycle, enabling faster iteration and impact delivery. (2) Develop science-based solutions to optimize seller engagement channel strategies. (3) Build and scale end-to-end AI-native recommendation models using generative AI and ML to identify critical seller challenges and unlock business growth opportunities. (4) Collaborate with stakeholders to transform business insights into rigorous scientific solutions.

Advertising is a complex, multi-sided market with many technologies at play within the industry. The industry is rapidly growing and evolving as viewers are shifting from traditional TV viewing to streaming video and publishers are increasingly adding video content to their online experiences. Amazon’s video advertising is a rising competitor in this industry. Amazon’s service has differentiated assets in our customer & audience insights, exclusive video content, and associated inventory that position us well as an end-to-end service for advertisers and agencies. We are innovating at the intersection of advertising, e-commerce, and entertainment. Amazon Publisher Monetization (APM) is looking for a a passionate and experienced scientist who is adept at a variety of skills; especially in generative AI, computer vision, and large language models that will accelerate our plans to maximize yield via AI-driven contextual targeting, Ads syndication and more. The ideal candidate will be an inventor at heart, they will provide science expertise, rapidly prototype, iterate, and launch, foster the spirit of collaboration and innovation within our larger sister teams and their scientists, and execute against a compelling product roadmap designed to bring AI-led science innovation to solve one of the most challenging problems in advertising. Key job responsibilities This role is focused on shaping our approach to the solving the trifecta of advertising - serving the right ad to the right viewer at the right moment - delivering engaging ads for viewers, improved performance for advertisers, and maximizing the yield of our supply inventory. Responsibilities include: * Partner deeply with Product and Engineering to develop AI-based solutions to generating contextual signals across both video (VOD and Live) and display ads. * Drive end-to-end applied science projects that have a high degree of ambiguity, scale, complexity. * Provide technical/science leadership related to computer vision, large language models and contextual targeting. * Research new and innovative machine learning approaches. * Partner with Applied Scientists across the broader org to make the most of prior art and contribute back to this community the innovation that you come up with.