Careers

Amazon's Worldwide Grocery Stores (WWGS), Data & Science team is seeking an Applied Scientist to join our Sales & Operations Planning (S&OP) and Supply Chain Science team. In this role, you will help build forecasting models that drive labor planning across the Amazon Grocery Network, where forecast misses can lead directly to staffing inefficiencies, higher costs, and degraded customer experience. You will contribute to the development and deployment of demand and labor forecasting models using Time-series, Bayesian and Structural methods, and Machine Learning. Senior scientists on the team will partner with you to scope problems and review designs, giving you room to build depth in forecasting science and production ML. You will also work directly with engineering partners, product owners, and business stakeholders, so you will see how your models change the decisions they make. Forecasts directly inform downstream labor and capacity decisions, so understanding how errors affect stakeholders is as important as improving accuracy. You will participate in design and roadmap discussions, communicate clearly with technical and non-technical partners, and develop judgment about the trade-offs in the systems you contribute to. We are investing in Generative AI to advance forecasting workflows, moving from human-in-the-loop to AI-in-the-loop decision support. Opportunities include automating forecast overrides for known events, identifying persistent bias, and augmenting planner and scientist judgment with agentic tools. Key job responsibilities - Develop, evaluate, and deploy components of our demand and labor forecasting models, including statistical time-series, Bayesian, and machine-learning models with distributional objectives, with input and guidance from senior scientists. - Translate business problems into well-defined scientific solutions with clear objectives, constraints, and success metrics, partnering with senior scientists on the more ambiguous ones. - Analyze forecast performance and downstream impact on labor planning and capacity decisions; develop metrics that reflect business outcomes, not only forecast accuracy. - Prototype and evaluate Generative AI approaches in our forecasting workflows and help productionize the ones that succeed. - Partner with engineering teams to produce models, contribute to data pipelines, and build scalable, maintainable forecasting systems. - Monitor deployed models, investigate performance issues, and continuously improve model quality and calibration. - Communicate technical concepts and recommendations clearly through documentation, presentations, and design reviews with scientists, engineers, product managers, and business leaders. - Contribute to the internal scientific community through knowledge sharing and, where appropriate, research publications.

Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software - Publish research publications at internal and external venues. About the team The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.

At Amazon, we’re inventing on behalf of customers, and with Amazon Leo, we’re redefining what global connectivity looks like. Our mission is to deliver fast, affordable broadband to unserved and underserved communities around the world through a constellation of low Earth orbit (LEO) satellites. Every system we build helps connect people to education, healthcare, opportunity, and each other. As a Data Scientist, you will be responsible for developing advanced analytics and machine learning solutions for user terminals. You will develop predictive models to proactively identify possible user terminal failures in the field. You will work in a collaborative environment with a multi-disciplinary team, including constellation, RF, antenna, silicon, algorithm, and software engineers. Key job responsibilities As a Data Scientist, you will develop analytic tools for a team developing current and future user terminals. Your responsibilities include: • Develop statistical and analytical tool to enable the regression decision from on-orbit and lab measurement of user terminals • Publish documents and create compelling visualizations and presentations to communicate insights to stakeholders • Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs • Develop scalable visualizations for analysis of user terminal performance • Work closely with constellation, RF, antenna, silicon, algorithm, and software engineers to root-cause the failures using data as the primary tool • Drive consensus on metrics and analysis approaches to support product development strategy Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. A day in the life As a Data Scientist in the LEO Customer Terminal Team, you will work daily with satellite constellation, algorithm, RF, antenna, silicon, hardware, and software teams in a collaborative environment. Your focus will be using data as an intelligence source to enable design decisions for the team. About the team The LEO Customer Terminal team is responsible for developing both outdoor and indoor devices that enable customers to access internet service via the LEO satellite network. We own the entire process from early prototypes through mass production, including requirements documentation, architecture definition, hardware development, algorithm development, and all integration and verification testing.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Research Scientist II Job Location: New York, New York Job Number: AMZ9898222 Position Responsibilities: Interact with various software and business groups to develop an understanding of their business requirements and operational processes. Utilize acquired knowledge and business judgment to build scalable machine learning systems, optimization models and operational tools to improve the bottom line. Build quantitative mathematical models to represent a wide range of supply chain, transportation and logistics systems. Implement these models and tools using modeling languages and engineering code in software languages such as Python, C++, or JAVA. Gather required data for analysis and mathematical model building by writing ad-hoc scripts and database queries. Perform quantitative, economic, and numerical performance analyses of these systems under uncertainty using statistical and optimization tools. Create computer simulations to support operational decision-making. Identify areas with potential for improvement and work with internal teams to generate requirements to realize improvements. Design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. Create software prototypes to verify and validate the devised solutions methodologies. Integrate prototypes into production systems using standard software development tools and methodologies. Position Requirements: Master's degree or foreign equivalent degree in Operations Research, Computer Science, Engineering, Mathematics, or a related field and one year 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 Operations Research, Computer Science, Engineering, Mathematics, 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 one year of experience. Must have one year of research or work experience in the following skill(s): (1) programming with a major programming language including Java, C++, C#, C, or Python; and (2) formulating and solving both discrete and continuous optimization problems. 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 $158,440/year to $212,800/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

As a member of the CMT team, you'll play a key role in the evolution of our Competitive Monitoring systems to solve significantly complex and interesting technical challenges in machine learning, large language models in production, and recommender systems to name a few. The team's work directly impacts customer experience at a worldwide scale. Key job responsibilities Key job responsibilities 1. Research the problem domain and come up with various approaches to solve the problem. 2. Be willing to experiment quickly and fail fast. 3. Collaborate with engineers to come up with the right end to end solution to the business problems. 4. Ideate on future roadmap for science in CMT 5. Be willing to roll up your sleeves and learn core topics outside applied science, for example ML engineering A day in the life A typical day might involve (a) working on ideas for improving models around product similarity or price recommendations, (b) working closely with other scientists and our ML engineers to ensure that the best models are in production, (c) writing good maintainable code that can be reused and reproduced, (d) sharing your work across CMT and beyond via technical writings and presentations

We are looking for an seasoned Applied Scientist to design, build, and deploy the ML/AI models that power our decision intelligence platform. You will work at the intersection of causal inference, time-series forecasting, anomaly detection, and LLM-based reasoning — all applied to real operational problems with measurable business impact. Key Job Responsibilities Decision Intelligence Models - **Causal inference & root cause analysis:** Build models that decompose fleet-wide metric movements into root causes, distinguishing correlation from causation across operational dimensions (site, service, failure mode, time) - **Dose-response modeling:** Develop models that learn the quantitative relationship between intervention intensity and outcome magnitude - **Forecasting & projection:** Build time-series models that project metric trajectories under different intervention scenarios, enabling "if we do X, expect Y by date Z" recommendations - **Anomaly detection & trend identification:** Develop multi-variate anomaly detection that distinguishes signal from noise in noisy operational data, and identifies emerging patterns before they become crises - **Confidence calibration:** Build and maintain calibrated confidence scores for recommendations, ensuring the system knows what it knows and what it doesn't - **Outcome attribution:** Design experiments and causal methods to measure the true impact of interventions LLM Integration & Reasoning - **Structured reasoning:** Design LLM prompting architectures that reliably transform operational data into executive-quality narrative summaries, decision framings, and recommendation rationales - **LLM evaluation:** Build evaluation frameworks that measure LLM output quality (accuracy, actionability, calibration) and detect degradation over time - **RAG systems:** Design retrieval-augmented generation systems that ground LLM outputs in operational data, historical playbooks, and institutional knowledge - **Progressive autonomy:** Design the trust-calibration system where AI gradually earns expanded authority based on demonstrated accuracy over time Research & Production - **End-to-end ownership:** Take models from research through production deployment — you ship, you monitor, you iterate - **Experimentation:** Design A/B tests and quasi-experiments to validate model improvements and measure business impact - **Stakeholder communication:** Translate complex scientific results into actionable insights for non-technical senior leaders

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 subscriptions such as Apple TV+, HBO Max, Peacock, 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 team member, 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 As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!

Would you like to work on developing AI systems models for one of the largest transactional distributed systems in the world? How about working with customers and peers from the entire range of Amazon's business and Science on complex real world problems, backed with high volume data ? Whether you're passionate about building highly scalable and reliable systems or a scientist who likes to solve business problems, Amazon Tax Platform Services is the place for you. We are responsible for the tax calculation platform, providing the core services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital, globally. We seek to provide the correct tax amounts to the customer when placing their Amazon order, and ensure all records are stored safely to meet tax law requirements around the globe. 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, and each one needs to be accurate. As an Applied scientist, you will provide machine learning leadership to the team that helps increase the accuracy of Tax classification based product information in Amazon catalogue making it the biggest and most challenging tax classification using Machine learning models globally. You will work with large language models, to build various machine learning models to predict accuracy of human's on specific tasks, reason with large volumes of systems and legislative changes to identify causal determinants, apply generative AI to model outcomes from sparse data. You will help us innovate different ways to enhance tax classification experience for our global customers. You will need to be entrepreneurial, work in a highly collaborative environment with SDEs, Product managers and businesses. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.

Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud. With AWS you can requisition compute power, storage, and many other services, gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly, with hundreds of thousands of companies in over 190 countries on the platform. The Sales Insights Analytics and Data Science (SIADS) team is looking for a Senior Applied Scientist to take a high-impact, senior technical role on our Data Science team. We build the machine learning and GenAI products that help the AWS Sales organization grow. Our work spans GenAI agents that answer sales questions in natural language, knowledge graphs, recommendation systems, synthetic controls, account prioritization models, and more. As a Senior Applied Scientist, you will own ambiguous, high-value problems end to end, from framing the question with business leaders through to a deployed model that changes how the field operates. You will set technical direction for problems that don't yet have a clear approach, choose the right method rather than the familiar one, and raise the bar for the science across the team. You will partner directly with customers across AWS Sales to understand the challenges they face and deliver solutions they trust and adopt. You will do this alongside a team of talented scientists working on some of the hardest and most impactful problems at the fastest-growing cloud provider in the world. You will have significant room to decide where to focus your efforts and to shape the direction of the work. You must be an expert in advanced quantitative and machine learning methods, and equally strong at synthesizing and communicating insights to audiences of varying technical sophistication. You will influence decisions well beyond your own projects, and you will help grow the scientists around you through mentorship and technical leadership. Key job responsibilities * Own the full lifecycle of complex science problems: problem framing, data exploration, method selection, modeling, evaluation, and production deployment. * Set technical direction on ambiguous problems and make the design decisions that others build on. * Partner with business stakeholders across Sales to turn open-ended business questions into well-scoped science, and translate results into recommendations leaders act on. * Raise the scientific bar across the team through design reviews, mentorship, and hands-on guidance. * Communicate methods, trade-offs, and results clearly to both technical and non-technical audiences. * Use Python, PySpark, and SQL for data analysis and model development. About the team Diverse Experiences AWS 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 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 empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity, inclusion) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. AWS Sales, Marketing, and Global Services (SMGS) 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. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

We are seeking a Sr. Data Scientist, to join Amazon Publisher Cloud (APC) team. APC is a game-changing new service, that operates at the intersection of advertising, secure signal collaboration, and cloud services. In this role you will be a key member of an entrepreneurial team tackling some of the most exciting and complex opportunities in digital advertising. The ideal candidate will have deep curiosity and creativity to build data science based solutions. Should demonstrate ability to incorporate latest tech, tools, and methodologies like generate AI and LLMs to enhance our product offerings. Lastly, have experience and comfort working with product, engineering, and Data Science peers within and across teams. Key job responsibilities In this role, you'll develop sophisticated methodologies and models that enable secure data collaboration between publishers and advertisers while maintaining privacy and data governance standards. - Design and implement experimental frameworks to validate Clean Room collaboration methodologies and measure their effectiveness - Develop statistical models and algorithms that power privacy-preserving data analysis capabilities - Lead end-to-end analysis projects to derive actionable insights from cross-party data collaborations - Partner with product teams to translate business requirements into technical solutions - Create reproducible analysis frameworks and documentation A day in the life - Meet with Product Managers to scope requirements for a new cross-publisher audience overlap analysis feature - Write and test code for a new measurement methodology that enables stakeholders to understand campaign effectiveness while preserving user privacy - Design and document statistical approaches for a new clean room collaboration use case - Conduct deep-dive analyses and run experiments to validate new methodologies against industry standards - Present findings and recommendations to leadership and stakeholders - Contribute to the team's technical roadmap and architecture decisions About the team APC Team comprises of smart, skilled, and driven professionals across leadership, product, engineering, data science, business development, and customer success function. We sit within Amazon Publisher Services (APS) business, which helps digital publishers around the world build and grow thriving businesses. We provide services and advanced technologies to web, mobile app and advanced TV publishers of all sizes, including many of comScore’s global top 100, to help them monetize their content with demand from multiple programmatic buyers.