Careers

Amazon Prime’s Science organization leads the Research & Development towards innovation for Amazon Prime. Amazon Prime is the backbone of Amazon’s consumer business and aspires to be the world’s most engaging, satisfying, and loved membership program, driving growth and profitability. The program serves over 200 million members across 25 countries and is key to Amazon’s customer growth and engagement. Prime Science innovates in Artificial Intelligence and Economics, to develop algorithms and systems for automated marketing, personalization, targeting, and decisioning. To lead Prime’s growth and impact through science and innovation, we are seeking a Principal Applied Scientist, Prime Science, to create and deliver Machine Learning innovation both for customer facing and internal solutions. To be successful in this role you should be recognized as an industry expert who has experience defining a long-term science vision, driven fundamentally from the needs of customers, translating that direction into specific plans for research scientists, applied scientists, engineering, and product teams. This is a role that combines science leadership, organizational ability, technical expertise, product focus, and business understanding. Prime is committed to diversity, equity, and inclusion and recognizes that our ability to serve our members is contingent on having diverse backgrounds, ideas, and ways of working on our team. This leader plays a key role as a member of the Prime worldwide leadership team to set the right organizational vision, standards, and mechanisms to ensure Prime is the best place for top talent to thrive. Key job responsibilities - Own and drive the most complex and strategic solutions across the business; responsible for many billions in revenue. - Act as a thought leader and forward thinker, anticipating obstacles to success and helping avoid common failure modes. - Research, build, and deploy innovative machine learning solutions; working across all technical disciplines. - Partner with science, engineering, and product leaders across the business to identify and deliver innovative machine solutions; identify new opportunities, define the vision and execute solutions that continually delight customers. - Hire, mentor, and guide senior scientists; partner with engineering leaders to build efficient and scalable solutions.

We are seeking an exceptional Managing Economist to lead our Japan Stores Economics team at Amazon. We work in a wide range of areas that are critical to our customers and businesses, including speed, selection, pricing, and customer growth. This role offers a unique opportunity to shape Amazon Japan's key business decisions and growth strategies through economic principles and econometric science. Key job responsibilities • Lead, mentor, and promote a team of economists, fostering a culture of customer obsession, innovation, and analytical rigor. • Proactively drive science-based strategic decision makings across Japan businesses. • Bar raise science and make critical prioritization and resource allocation decisions to ensure the team delivers the highest impact. • Collaborate with product, engineering, and science teams in Japan and around the global to drive innovation together. • Represent the economist team in global forums and executive-level meetings. About the team Japan Stores Economics team is the central team for Amazon Japan's economic science. We are a compact team of highly skilled Ph.D. economists who work on some of the most impactful problems in Japan, including selection, delivery speed, pricing, and customer growth. We are not merely an internal consulting team -- we proactively work with the business teams to identify opportunities and shape how our business operates. We are a force-multiplier -- we bring together product, engineering, and finance teams to drive complex projects and deliver innovations to our customers.

We’re working to improve shopping on Amazon using the conversational capabilities of LLMs, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role you will influence our team’s science and business strategy with your analyses. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state of the art machine learning research. You will be owner of the solutions that you create, you will lead junior members of the team, and you will work closely with Software Development Engineers to deploy the models into production. Your solutions will drive the technology behind agentic solutions, automated evaluations, and sophisticated RAG at Amazon.

mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in forecasting and risk modeling to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and air planes to transport millions of packages per day as well as other freight between warehouses, vendor facilities, and customers, on time and at low cost. The mmPROS Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative forecasting, risk quantification, and other machine learning models to decide the optimal long-term and short-term strategy for truck capacity procurement and other planning problems. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on machine learning and optimization problems, and you will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities - Design, develop, and implement forecasting models, risk models, and other machine learning models to inform our hardest planning decisions. - Implement machine learning and risk models in Amazon's production software. - Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems. - Lead complex modeling and data analyses to aid management in making key business decisions and set new policies. - Write documentation for scientific and business audiences. About the team This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We aim to leverage cutting edge technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges. Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

WWGS (Worldwide Grocery Stores) organization leads the innovation of Amazon’s omni-channel grocery offerings (Fresh, Whole Foods, 3P). In this space, Amazon aims to delight customers by providing broad selection, competitive prices, best-in-class delivery, convenient in-store/pickup options across regions, and an end-to-end shopping experience that makes it easy for customers to discover what they love and build complete grocery baskets. The Grocery Management Science team in WWGS is looking for a Data Scientist to help create and drive the long-term vision for how we manage selection of products for our cross-banner grocery brands globally. As a Data Scientist on our team, you will work with product managers, vendor managers, software development engineers (SDEs), and other scientists to help the WWGS organization determine optimal selection breadth and depth for our online and physical stores. You will also develop and extend models of key customer behavior and preferences by quantifying expected demand, derive optimal pricing and promotion strategies and optimization approaches that produce selection recommendations that delight our customers and meet our real-world constraints. You will be expected to own the the full lifecycle of your projects from devising methodological approaches, implementation, validation, and working with SDEs to integrate into production systems. A successful candidate will be able to partner effectively with both business and technical teams, including clear communication of results and the ability to influence a variety of stakeholders. The ideal candidate will posses strong knowledge of causal estimation techniques, and be curious and excited to apply these in challenging real-world settings. Key job responsibilities * Interact with engineering, operations, science, and business teams to develop an understand and domain knowledge of processes, system architectures, and business requirements. * Develop scalable models to generate selection models. * Create prototypes, simulations, and experiments to test devised solutions. * Advocate technical solutions to business stakeholders, engineering teams, and executive-level decision makers * Work closely with engineers to integrate models into production systems.

The Worldwide Capacity Planning team is looking for a Research Scientist for their Forecasting Science team. Here you'll develop cutting-edge algorithms that transform complex analytical insights into powerful business solutions. You'll design and implement innovative and automated end-to-end forecasting solutions to support planning, and address critical demand challenges and service quality metrics. The ideal candidate will be an innovative problem-solver with exceptional communication skills, and passionate about turning data into meaningful organizational transformation, leveraging techniques like machine learning, econometric modeling, time series forecasting, statistical inference, and optimization to directly impact our bottom line and elevate our global customer service capabilities. Our science team is tasked with designing algorithms and systems for all stages of the labor planning process for Amazon customer service, from long-term headcount planning optimization, to short-term scheduling and real-time routing. As a research scientist, you will work on cutting edge research using a combination of optimization, simulation, stochastic modeling, statistics, and/or machine learning to optimize one of the most complex service systems in the world. Key job responsibilities - Design and develop advanced models with a combination of optimization, computer simulation, stochastic modeling, statistics, and/or machine learning techniques to create scalable solutions for business problems in customer service labor planning. - Collaborate with product, software engineering, research science, data engineering, and business leaders to build appropriate business and technical solutions. - Conduct research, prototype, and experiment with models and solutions using scripting languages such as Python. Participate in the production-level deployment of these solutions. - Use the best practices in science: data integrity, design, test, and implementation and documentation. - Contribute to Amazon's Intellectual Property through patents and internal and external publications. - Mentor and guide junior members in the team. 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 rapidly adapt 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 Worldwide Capacity Planning optimizes capacity across operations sites that help minimize customer wait time and route customers to the associate who can best resolve their issue, on the first contact. We build forecasting models and optimization tools that help predict the hourly capacity requirement, including when there are new device or game launches, or when there is a special event, such as Prime Day.

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 limit. 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. 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 Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.

Amazon Business (AB) is dedicated to serving the needs of business customers by building the most innovative B2B marketplace in the world. As part of Amazon Business Europe (ABEU), we’re scaling our business by integrating cutting-edge technology, advanced data science, and robust engineering solutions to create exceptional experiences for business customers across the EU. We are seeking a Sr. Manager of Data Science to lead a multi-disciplinary team driving innovation and operational excellence. This role is pivotal to our mission, combining strategic vision, hands-on leadership, and scientific expertise. You will manage a diverse team of data scientists, business intelligence and data engineers, working collaboratively to deliver high-impact scientific solutions and scalable systems to improve customer experience and drive business growth. The role focuses on identifying and solving ambiguous, high-value problems using state-of-the-art methodologies in machine learning (ML) as well as developing self-service data platforms for internal analytics. Key job responsibilities • Strategic Leadership: Define and execute the scientific vision for ABEU, aligning with broader Amazon Business goals. Drive cross-organizational initiatives, identifying opportunities to leverage data science and advanced analytics to solve critical business challenges. Partner with senior leaders to prioritize programs and align resources with strategic objectives. • Team Development: Hire, develop, and mentor a diverse team of scientists and engineers, fostering a culture of innovation, learning and excellence. • Science and Innovation: Design and implement cutting-edge ML models, analytics systems, and scalable architectures to support B2B e-commerce. Explore novel scientific approaches and contribute to advancements in areas such as sales automation, product recommendation, pricing optimization, and customer segmentation. Stay abreast of industry developments to inspire and implement state-of-the-art solutions, particularly in GenAI. • Stakeholder Engagement: Represent scientific and technical initiatives to senior leadership, articulating trade-offs and driving consensus. Collaborate across geographies and functions to integrate AB data into tools and systems, improving customer experience and operational scalability. • Operational Excellence: Develop the data foundation and metrics to enhance operational transparency and decision-making. Manage day-to-day technical operations, ensuring quality and efficiency across data pipelines, tools, and models.