Careers

Lead a team of economists, data scientists, and applied scientists in Amazon's People Experience and Technology organization. This role combines advanced economic research, team leadership, and strategic planning to drive innovations that enhance the employee experience and organizational effectiveness at Amazon. You'll develop and implement sophisticated causal and predictive models, leveraging economic theory, behavioral science, and advanced analytics to identify improvements in people processes and policies. Working closely with cross-functional partners, you'll translate complex economic insights into actionable recommendations for senior leadership. Key job responsibilities As a Manager III, Economist, you will lead a team of economists, data scientists, and applied scientists working to solve complex economic and scientific problems that have high business and customer impact. You will be responsible for building causal and predictive models, working with engineering teams to deploy science models to products, leveraging economic and data science workflows, and driving innovations that deliver measurable results for Amazon customers. The key responsibilities of the position include: Leadership & Team Management: Independently manage and develop a diverse team of economists and scientists, 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 & Economic Direction: Partner with stakeholders and leadership to define and execute the economic research vision for your team; Lead the development of causal and predictive models, leveraging emerging technologies and novel identification strategies; Drive the implementation of economic analysis workflows and simulation frameworks; Bridge the gap between economic theory, empirical analysis, 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 methodologies; Establish processes that enable consistent delivery and quality of economic research; 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 economic insights to technical and non-technical audiences; Influence economic research and analytics practices across the organization; Build strong partnerships with stakeholders across different business units; Present complex economic 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 uses economic theory, causal inference, 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. We are an interdisciplinary team combining expertise in economics, social science, and data science to develop and deliver solutions that measurably achieve this goal.

The Amazon Regulatory Intelligence, Safety, and Compliance (RISC) team is seeking an exceptional Applied Scientist to tackle complex compliance challenges. In this high-impact role, you will leverage your deep technical expertise and customer-obsessed mindset to design and evaluate state-of-the-art algorithms in risk modeling, computer vision, and natural language processing. You will translate complex business requirements into well-defined science problems and work collaboratively with product, engineering, and business stakeholders to drive real-world impact. Staying at the forefront of applied machine learning, you will continuously adapt your skills to tackle new challenges. Contributing to Amazon's scientific thought leadership, you will author high-quality research papers for internal and external conferences. This is an opportunity to apply your technical skills in a fast-paced, highly collaborative environment, making a meaningful difference in the lives of Amazon's customers. If you have a passion for solving complex problems and a customer-centric approach, we encourage you to apply for this exciting role. Key job responsibilities - Explore the use of reinforcement learning, multi-agent systems, and meta-learning to build autonomous AI agents that can adapt to new challenges and support complex decision-making. - Design and evaluate state-of-the-art algorithms and approaches in risk modeling, using techniques such as graph neural networks, deep learning, and boosted trees to detect anomalies, fraud, and policy violations. - Develop advanced multi-modal and large language models to classify product content, understand customer intent, and retrieve relevant information. - Collaborate closely with product managers, engineers, and business stakeholders to validate hypotheses, drive adoption, and maximize the real-world impact of your work. - Translate complex product and customer experience requirements into well-defined, measurable science problems and KPIs, contributing to Amazon's scientific thought leadership through high-quality research papers. A day in the life - Understanding customer problems, project timelines, and team/project mechanisms - Proposing science formulations and brainstorming ideas with team to solve business problems - Writing code, and running experiments with re-usable science libraries - Reviewing labels and audit results with investigators and operations associates - Sharing science results with science, product and tech partners and customers - Contributing to team retrospectives for continuous improvements - Participating in science research collaborations and attending study groups with scientists across Amazon

Passionate about books? The Amazon Books Store Experience team is looking for a talented Economist to help invent, design, and measure innovative science solutions to make it easier for millions of customers to find the next book they will love. Key job responsibilities In this role you will: - Partner with cross-functional teams to leverage advanced economic and causal modeling techniques, to drive business insights and decision-making. - Conduct in-depth research and analysis on large, complex data sets to understand customer behavior, pricing dynamics, and the incremental impact of business programs and initiatives. - Design, implement, and maintain scalable econometric and machine learning solutions to automate and improve key measurement and optimization capabilities. - Effectively communicate analysis, insights, and recommendations to influence senior leadership, business strategy and roadmap prioritization. About the team The Books Store Experience team is a core team developing the frameworks and technologies used by dozens of partner teams to develop the best shopping experience for our books customers. The books organization is the oldest organization at Amazon serving customers from the very beginning. This team has a wealth of experience in Amazon and is constantly evolving the technologies we use in order to best serve our customers.

The Amazon Selection and Catalog Systems team (ASCS) builds global selection and catalog management systems. The Selection Monitoring team is responsible for building the biggest product selection on the planet to satisfy our customers’ all shopping needs. We build platforms, systems and tools to create and take advantage of datasets that contains billions of records, use the latest machine learning, data processing technologies and a broad set of AWS technologies. In order to drive the expansion of Amazon selection, we use cluster-computing technologies such as MapReduce and Spark to process billions of products and find the products/brands not already sold on Amazon. We work with structured and unstructured content such as text and images and apply Machine Learning algorithms such as Clustering, Natural Language processing, Fuzzy matching and Image processing at a massive scale. We are looking for a Manager, Applied Science to tackle ambiguous problems in the areas of data processing, machine learning algorithms and distributed systems of cloud-scale. You are expected to take ownership, dive deep and drive solutions from developing prototypes, doing experiments, design to coding, testing and deployment. The role demands innovation and expects you to push the boundaries. You will get opportunity to work with many tech teams and business teams within Amazon and deliver solutions that will have an impact to both Amazon top-line & bottom line.

Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As an Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities - You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives. - You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc. - Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined. - You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. - You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones. - You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members. - You set standards and proactively drive components to use and improve on state-of-the-art techniques. - You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the next-level. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Key job responsibilities * Partner with laboratory science teams on design and analysis of experiments * Originate and lead the development of new data collection workflows with cross-functional partners * Develop and deploy scalable bioinformatics analysis and QC workflows * Evaluate and incorporate novel bioinformatic approaches to solve critical business problems About the team Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

The Customer Engagement Technology (CET) team leads AI/LLM- (Large Language Model) driven customer experience transformation using task-oriented dialog systems. We develop multi-modal, multi-turn, goal-oriented dialog systems that can handle customer issues at Amazon scale across multiple languages. These systems are designed to adapt to changing company policies and invoke correct APIs to automate solutions to customer problems. Additionally, we enhance associate productivity through response/action recommendation, summarization to capture conversation context succinctly, retrieving precise information from documents to provide useful information to the agent, and machine translation to facilitate smoother conversations when the customer and agent speak different languages. Key focus areas include: - Task-Oriented Dialog Systems: Building reliable, scalable, and adaptive LLM-based agents for understanding intents, determining eligibilities, making API calls, confirming outcomes, and exploring alternatives across hundreds of customer service intents, while adapting to changing policies. - Lifelong Learning: Researching continuous learning approaches for injecting new domain knowledge while retaining the model's foundational abilities and preventing catastrophic forgetting. - Agentic Systems: Developing a modular agentic framework to handle multi-domain conversations through appropriate system abstractions. - Complex Multi-turn Instruction Following: Identifying approaches to guarantee compliance with instructions that specify standard operating procedures for handling multi-turn complex scenarios. - Inference-Time Adaptability: Researching inference-time scaling methods and improving in-context learning abilities of custom models to enable real-time adaptability to new features, actions, or bug fixes without solely relying on retraining. - Context Adherence: Exploring methods to ground responses in specific customer attributes, account information, and behavioral data to prevent hallucinations and ensure high-fidelity responses. - Policy Grounding: Investigating techniques to align bot behavior with evolving company policies by grounding on complex, unstructured policy documents, ensuring consistent and compliant actions. - End-to-End Dialog Policy Optimization: Researching alignment approaches to optimize successful dialog completions. - Scalable Evaluations: Developing automated approaches to evaluate the quality of experience, and correctness of agentic resolutions. Key job responsibilities - Research and development of LLM-based chatbots and conversational AI systems for customer service applications. - Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation. - Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. - Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of chatbot systems. - Conduct experiments and evaluations to measure the performance of developed models and systems to identify areas for improvement. - Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. - Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to adapt rapidly in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment. If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Benefits Summary: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, as well as associate-facing products that support our customer service associate workforce.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As a Senior Data Scientist on this team you will: - Lead Data Science solutions from beginning to end. - Deliver with independence on challenging large-scale problems with complexity and ambiguity. - Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data. - Build Machine Learning and statistical models to solve specific business problems. - Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance. - Analyze historical data to identify trends and support optimal decision making. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose effective solutions for the business problems you define. - Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE

Amazon Web Services (AWS) is looking for a Principal Applied Scientist to join the Amazon Q team. Q is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive. You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, hands-on innovation, and deep collaboration with engineering teams to bring research into production. Key job responsibilities Lead the design and development of foundational models and intelligent agent architectures tailored to enterprise use cases. Partner with engineering, product, and UX teams to integrate generative AI into the Amazon Q assistant. Drive experimentation to improve model accuracy, safety, latency, and cost efficiency. Mentor other scientists and engineers, helping raise the technical bar across the team. Contribute to and publish in top-tier conferences or file patents based on novel research contributions. About the team Amazon Q is a generative AI-powered assistant that helps employees become more productive by answering questions, generating content, summarizing data, and automating workflows using enterprise information. Our team builds the intelligence behind Q, leveraging large language models, retrieval-augmented generation, and agentic architectures to orchestrate complex workflows securely and at scale. We’re focused on building systems that reason, plan, and act across multiple modalities and business tools. As part of AWS’s broader Agentic AI initiative, we’re shaping the future of enterprise AI—empowering organizations to solve problems faster, reduce operational overhead, and unlock new levels of efficiency and decision-making.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As an Applied Scientist on this team, you will: - Be a strong contributor to Machine Learning; lending effort within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE