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MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Economist III Job Location: New York, New York Job Number: AMZ9511152 Position Responsibilities: Work with senior management and other scientists on key business problems faced in cloud computing and operations. Utilize methods at the frontier of economics and time-series econometrics to develop formal models to understand the past and the present, predict the future, and identify relevant risks and opportunities. Build econometric models of dynamic systems using Bayesian times-series statistical methods and leveraging big data tools. Develop and implement statistical models for risk assessment and capacity management in cloud infrastructure. Formalize problems using rigorous science to solve business issues. 40 hours / week, 8:00am-5:00pm, Salary Range: $226,782/year to $236,900/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. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist II Job Location: New York, New York Job Number: AMZ9970940 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. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. 40 hours / week, 8:00am-5:00pm, Salary Range: $172,400/year to $223,400/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. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON ADVERTISING LLC Offered Position: Applied Scientist II Job Location: New York, New York Job Number: AMZ9935275 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. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. 40 hours / week, 8:00am-5:00pm, Salary Range: $172,400/year to $223,400/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. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

Are you interested in leading growth initiatives for one of Amazon’s most significant and fastest growing businesses? Selling Partners offer hundreds of millions of unique products and are a critical to delivering on our vision of offering the Earth’s largest selection and lowest prices. The Amazon Marketplace enables over 2 million third-party selling partners in eleven marketplaces to list their products for sale to Amazon customers across the world. Within our WW Marketplace business, International Seller Services (ISS) oversees the recruiting and development of Selling Partners for all of our international marketplaces (e.g. UK, Germany, Japan, Middle East etc.). ISS also enables global selling, helping Sellers in one country expand and sell internationally. Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, the Central Science Team of Amazon's International Seller Services has an exciting opportunity for you as an Applied Science Manager. We are seeking an experienced science leader who is adept at a variety of skills; especially in generative AI, computer vision, and large language models that will help international sellers succeed as they sell on Amazon. The right candidate will provide science leadership, establish the right direction and vision, build team mechanisms, foster the spirit of collaboration and innovation within the org, and execute against a roadmap. This leader will provide both technical direction as well as manage a sizable team of scientists. They will need to be adept at recruiting, launching AI models into production, writing vision/direction documents, and building team mechanisms that will foster innovation and execution. Additionally, while the position is based in Seattle, this leader will interact with global leaders and teams in Europe, Japan, China, Australia, and other regions. Key job responsibilities Key job responsibilities Responsibilities include: * Drive end-to-end applied science projects that have a high degree of ambiguity, scale, complexity. * Provide technical / science leadership related to NLP, computer vision and large language models. * Research new and innovative machine learning approaches. * Recruit high performing Applied Scientists to the team and provide mentorship. * Establish team mechanisms, including team building, planning, and document reviews. * Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.

We're looking for a Research Scientist to join a team that builds the science behind how Amazon supports its 1.5M+ employees - from forecasting demand across HR services to optimizing how work gets routed and assigned in real time. You'll own high-impact operations research and causal inference work that directly reduces costs and improves the employee experience at global scale. In this role, you will: - Design and build simulation and optimization models that automate workforce scheduling, hiring, and task assignment across Amazon's HR contact centers and back-office operations - Develop causal inference frameworks to measure the true impact of policy changes, product launches, and AI-driven initiatives on employee experience and operational efficiency - Collaborate with senior leaders to translate complex analytical findings into actionable strategies that influence staffing, routing, and resource allocation decisions affecting thousands of associates - Push the boundaries of what's possible by combining operations research with machine learning and generative AI to solve novel workforce optimization problems This isn't a role where you'll be running standard analyses on repeat. You'll be building novel solutions - like contact center simulators that replicate real-world operations, scheduling optimizers that replace manual processes, and experiment frameworks that credibly quantify the impact of large-scale organizational changes. Your work will directly inform decisions made by VP and Director-level leaders who set the strategy for how Amazon supports its employees at scale. About the team We are a team of economists, research scientists, and data scientists within Amazon's People Experience and Technology Finance organization. Our mission is to make Amazon's employee support services smarter, faster, and more efficient through rigorous science - from forecasting models that drive hiring plans to simulation engines that optimize how HR services are delivered to Amazon's global workforce of 1.5M+ people. Our work runs in production, informs weekly planning decisions, and shapes resource allocation at scale. We value intellectual rigor, ownership, and collaboration — publishing at internal science conferences, maintaining shared codebases, and holding each other to high technical standards. You'll have real ownership from day one: framing problems, building solutions, and presenting results to senior leaders who act on your recommendations.

Amazon is seeking a world-class Sr. Applied Scientist to lead the development of next-generation object tracking systems for autonomous robots operating at Amazon's scale. In this role, you will architect robust, real-time tracking pipelines that fuse information across multiple sensor modalities — combining the rigor of classical estimation theory with the power of modern learning-based approaches to deliver tracking systems that are accurate, reliable, and scalable in complex, dynamic environments. Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. We leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Applied Scientist working on Tracking and Sensor Fusion, you will own the design and delivery of tracking systems that enable robots to maintain persistent, accurate awareness of objects, humans, and dynamic elements in their environment. You will bring deep expertise in multi-sensor fusion, Bayesian estimation, and Kalman filtering — paired with a strong command of modern learning-based tracking methods — to build systems that are both principled and adaptive. Your work will be foundational to safe and intelligent robot behavior: enabling downstream planning, navigation, and manipulation systems to operate with confidence in the presence of uncertainty and change. You will lead research that bridges classical state estimation with data-driven approaches, collaborating with world-class teams pushing the boundaries of robotic perception, autonomy, and human-robot interaction. Join us in building intelligent tracking and fusion systems that will define the future of autonomous robotics at scale. Key job responsibilities - Lead the research, design, and development of multi-object tracking (MOT) systems for autonomous robots, combining classical and learning-based approaches - Develop and deploy sensor fusion pipelines that integrate data from cameras, depth sensors, radar, IMUs, and other sensor modalities using principled estimation frameworks (Extended Kalman Filters, Unscented Kalman Filters, Particle Filters, factor graphs) - Pioneer learning-based tracking methods including neural data association, learned motion models, transformer-based trackers, and end-to-end differentiable tracking architectures - Design robust track management systems — including track initialization, association, occlusion handling, re-identification, and track lifecycle management - Develop and validate tracking systems that operate reliably in real-time under challenging conditions: occlusion, clutter, sensor noise, and dynamic scene changes - Collaborate closely with Perception, Navigation, Planning, and Controls teams to deliver integrated autonomy solutions - Establish benchmarks, evaluation frameworks, and safety validation protocols for tracking systems - Mentor scientists and engineers; foster a culture of scientific rigor, innovation, and high-impact delivery - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Every day, hundreds of thousands of Amazon associates show up to fulfill the promise we make to our customers. Behind the workforce decisions that support them — staffing, retention, scheduling, development — there should be science that doesn't just describe what happened, but explains why it happened and predicts what comes next. That's the work we do. PXT Central Science (PXTCS) is Amazon's internal research organization dedicated to bringing scientific rigor to people and workforce decisions at global scale. Our team sits within the part of PXTCS that focuses on Amazon's Tier 1 hourly populations — the associates at the heart of Amazon's operations. We are a multidisciplinary group of 15 economists, data scientists, data engineers, and research scientists united by a single mission: to transform complex operational challenges into actionable insights through rigorous causal analysis and predictive modeling that empowers data-driven workforce decisions. We are building something new — causal predictive models that go beyond traditional forecasting. Our models don't just tell leaders what will happen; they reveal why it will happen and what levers they can pull to change the outcome. This is the frontier where causal inference meets modern machine learning, and we need a scientist who can help us push it forward. As a Data Science Manager (DSM), you will lead a team of economists, scientists, and data engineers working to solve complex scientific problems that have high business and customer impact. You will be responsible for building structural and predictive models, leveraging data science workflows, and driving innovations that deliver measurable results for Amazon customers. You will work shoulder-to-shoulder with economists who deeply understand the causal mechanisms driving workforce dynamics and data scientists who know the operational landscape — and you will bring the technical creativity to expand what's possible. That means writing production-quality code that our partner engineering teams can implement into decision-making tools. It means exploring novel feature spaces — large language models, computer vision, and other emerging techniques — to unlock signal that traditional approaches miss. And it means doing all of this with the scientific rigor that causal claims demand. This role is built for someone who is entrepreneurial and energized by ambiguity — someone who sees a prototype model and immediately starts thinking about how to make it robust, scalable, and impactful. You will not just advance your own work; you will elevate the scientists around you. If you want to do science that directly shapes how Amazon supports its workforce — not in theory, but in production systems that leaders use to make better decisions every day — we'd love to talk. Key job responsibilities - Leadership & Team Management: Independently manage and develop a diverse science team, creating an environment that enables consistent delivery and innovation; Build and maintain a high-performing team that can operate effectively and autonomously; Drive strategic growth opportunities for team members, providing paths to demonstrate higher-level scope, impact, and leadership; Establish clear performance metrics and audit mechanisms to track and communicate team progress; Foster a team culture focused on bringing research to production and delivering customer value - Technical & Scientific Direction: Partner with stakeholders and leadership to define and execute the scientific vision for your team; Lead the development of structural and predictive models, leveraging emerging technologies and novel features; Drive the implementation of data science workflows and simulation frameworks; Bridge the gap between science, technology, and business requirements; Leverage the broader Amazon scientific community to enhance team capabilities and knowledge sharing - Strategic Planning & Execution: Define and maintain team structure, strategic direction, and owned technologies; Establish processes that enable consistent delivery and quality of scientific artifacts; Drive reasonable schedules and adjust priorities to ensure optimal outcomes; Create and implement audit mechanisms to track team performance against goals; Remove roadblocks and optimize team productivity - Communication & Influence: Create well-written documents to effectively communicate with technical and non-technical audiences; Influence science and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex scientific findings to senior leadership; Drive adoption of best practices and innovative solutions About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, machine learning, and Generative AI to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and UX to develop and deliver solutions that measurably achieve this goal.

The Catalog Services Product Knowledge team is seeking a Sr. Applied Science Manager for leading initiatives for understanding, and scaling organization of product schema information. Our vision is simple: build AI systems that are capable of a deep product understanding, so we can organize and scale the catalog metadata (schema) for Amazon e-commerce catalog worldwide. This is a complex problem because the magnitude of products entities (attributes, values, constraints) to be modeled to cover all the Amazon products worldwide. You will lead a team of experienced Applied Scientists (direct reports) to create models and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML and GenAI techniques that will scale our catalog artifacts with a high precision across countries and languages. The leader will drive investments in machine learning, natural language processing, GenAI, to solve real world problems at scale. The team's output affects the velocity at which we build product schema and support the largest e-commerce catalog and impact million of customers. The team builds solutions ranging from automatic generation of product metadata, classification of entities, validation of concepts against customer traffic, creation of agents solving complex tasks mimicking human decisions at high precision, etc; all these developments drive true understanding of products at scale. We are looking for an entrepreneurial, experienced Sr. Applied Science Manager who can turn a group of Machine Learning Scientists (PhD's in NLP, ML, GenAI) to produce best in class solutions. The ideal candidate has deep expertise in one or several of the following fields: Generative AI, Agents, LLMs, Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Natural Language Processing. S/he has a strong publication record at relevant academic venues and proven experience in launching products/features in the industry. Key job responsibilities In this team, you will: - Manage business and technical requirements, design, be responsible for the overall coordination, quality, productivity and will be the primary point of contact for world-wide stakeholders of programs and goals that you lead. - Partner with scientists, economists, and engineers to help deliver scalable ML scaled models, while building mechanisms to help our customers gain and apply insights, and build road maps for the projects you own. - Track service levels and schedule adherence, and ensure the individual stakeholder teams meet and exceed their performance targets. - Be expected to discover, define, and apply scientific, engineering, and business best practices. - Manage and develop Applied Scientists (direct reports with a respective team). About the team The team's mission is to infer knowledge, understand, and derive product schema for all Amazon products entering the Catalog. The work is critical to power drive policies on how products will be merchandised, guide Selling Partners, inform models how to infer attributes. All this information drives the navigational Taxonomy, Search and Detail Page experiences, impacting million of customers. This is an already formed team with experience leading programs spanning services and ML initiatives. The leader collaborates closely with Software Managers, Sr. Leaders, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

Do you want to shape the future of music discovery by building applied science solutions at Amazon scale? Join our Amazon Music team where you'll define and execute the applied science roadmap for catalog and search systems, directly impacting millions of customers worldwide. You'll work at the exciting intersection of large-scale content systems, applied science, and applying the latest advances in foundation models to build an intelligence layer on top of one of the world's largest music and podcast catalogs. As a Principal Applied Scientist, you'll drive innovation in music content understanding, leveraging foundational models to enrich catalog data intelligence and create breakthrough customer experiences. Your work will span across music catalog, search, and data systems teams, where success is measured by customer satisfaction, partner team success, and music labels' ability to share high-quality content seamlessly. Key job responsibilities - Lead the design and implementation of applied science solutions for large-scale music catalog systems, leveraging foundational models to enhance content intelligence and understanding - Define and execute the technical roadmap for Amazon Music catalog and search teams, driving architectural decisions across multiple systems and ensuring alignment with long-term business objectives - Design, propose, and collaborate on experiments that leverage rich music content for enhanced customer experiences in search, personalization, and recommendation systems - Drive technical excellence across three teams (music catalog, music search, music data systems) by conducting design reviews, setting engineering standards, and mentoring senior technical talent - Solve complex problems at the intersection of content systems and applied science, proactively identifying risks and implementing solutions that balance short-term deliverables with long-term architectural maintainability About the team The Amazon Music Catalog and Search team is responsible to help our customers discover the most relevant audio content including music, podcasts and audiobooks. The team invents technology at the intersection of the largest audio catalog in the world, applying latest advances in foundation models and proprietary data assets of Amazon Music. We build technology and products that is deployed worldwide but at the same time is customizable for local markets. We measure our success by the success of our customers, partners and audio content creators.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9442729 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: Bachelor'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 four years of experience as equivalent to the Bachelor’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 $163,322/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