Careers

The Decision Science team within Amazon Devices is seeking an experienced Senior Data Scientist to lead the development and implementation of sophisticated demand forecasting models and customer segmentation analyses that will shape our future product portfolio. Are you excited about making multi-million dollar decisions science- and data-driven? Are you interested in supporting Consumer Hardware device concepts from innovative idea to launch? Do you want to work on a science team focused on scaling a variety of econometric and machine learning models? This could be the role for you! The Decision Science team owns demand estimates and pricing recommendations of concept devices before customers know they exist. We support over 100 device-specific analyses a year on hardware and services ranging from Echo Frames to Kindle Paperwhite to Blink Video Camera. We apply science models to multi-million dollar, one-way door decisions. The successful candidate will excel at exploring and simplifying internal customer business problems, and delivering deliver solutions to those problems that can eventually scale to self service tools. Key job responsibilities As a Data Scientist III at Amazon Devices, you will play a crucial role in shaping our product strategy and launch plans through advanced pre-launch forecasting and customer segmentation analysis. Your primary responsibilities will include: - Develop and execute sophisticated conjoint surveys to gather critical consumer insights for upcoming device launches. - Build and refine demand models using conjoint survey data and historical sales information to produce accurate pre-launch forecasts for new Amazon devices. - Lead the advancement of customer segmentation analysis, identifying key characteristics and behaviors of device purchasers across different product lines. - Collaborate with cross-functional teams including Product Management, Marketing, and Finance to translate data-driven insights into actionable strategies for product development and go-to-market plans. - Design and implement machine learning algorithms to enhance the accuracy of demand forecasts and improve customer segment identification. - Stay current with the latest developments in data science techniques, particularly in the areas of conjoint analysis, demand modeling, and customer segmentation. - Mentor junior data scientists and contribute to the overall growth of the data science practice within Amazon Devices.

Amazon Sponsored Products is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to Amazon’s Selling Partners and key to driving their long-term growth. We deliver billions of ad impressions and clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving team with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. This position will be part of the Advertiser Growth organization within Sponsored Products. Our team focuses on launching innovative controls that help advertisers create and manage performant SP campaigns. We develop recommendations to help advertisers use these controls effectively and develop state-of-art ML based optimization services to represent our advertisers in the SP marketplace. We strive to improve the ability for advertisers to help shoppers discover relevant products on customer search, browse and detail pages. Key job responsibilities • Seek to understand in depth the Sponsored Products offering at Amazon and identify areas of opportunities to grow our business using AI/ML solutions. • Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. • Design and lead organization-wide ML roadmaps to help our Amazon shoppers have a delightful shopping experience while creating long term value for our advertisers. • Work with our engineering partners and draw upon your experience to meet latency and other system constraints. • Identify untapped, high-risk technical and scientific directions, and devise new research directions that you will drive to completion and deliver. • Be responsible for communicating our AI/ML innovations to the broader internal & external scientific community.

** This position is open to all candidates in NYC and Arlington, VA Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.

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 a Senior 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.

Are you excited about developing state of the art Machine Learning (ML) capabilities to power Amazon's robotic storage solutions? Are you looking for opportunities to build and deploy Machine Learning models on real problems at truly vast scale? At Amazon Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. The Robotic Storage Technologies (RST) team at Amazon Robotics is seeking a passionate, collaborative, hands-on Applied Scientist to develop algorithms that foster optimal choice selection in Amazon's next generation robotic storage systems. You will explore and leverage huge amounts of inventory and robotic transactional data from our growing network of warehouses across the globe. You will utilize a combination of machine learning, reinforcement learning, and optimization methods to drive high performance that scales and adapts under dynamic operating conditions. This work spans from early research and simulation of new ideas through deployment and continuous improvements as our solutions and Amazon's needs continually evolve. The ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses! Key job responsibilities - Research new ideas and contribute to the vision of our science roadmap. - Design and develop models and algorithms that perform at Amazon scale. - Work closely with software engineering teams to deploy your innovations. - Monitor, troubleshoot, and continuously improve production in performance. - Contribute to development of simulation and other forms of offline policy evolution. - Publish your work at major conferences/journals. A day in the life On a typical day in this role you will work to progress your research projects; meet with robotic storage engineering, systems, and solutions stakeholders; brainstorm with other scientists on the team and participate in team processes. You will follow your research projects though the entire life cycle of design, prototype implementation, evaluation, analysis, and you will communicate your findings and results through technical papers and reports. You will collaborate with software development teams to implement your ideas in production software services and design experiments to pilot your algorithms and models in Amazon's robotic warehouses. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. 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 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! About the team Robotic Storage Technologies (RST) owns automation of storage and retrieval solutions in Amazon's vast network of fulfillment centers across the globe. Our solutions are driven by fleets of hundreds of robots, and our customers are operations engineers and associates who help fulfill millions of Amazon.com orders per day. You will be part of a team of scientists embedded within the software organization that supports the solutions you help to deploy.

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Principal Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. They will lead research projects to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work well in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. About the team The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfillment on customer orders so that we fulfill all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. SCOT- Fulfillment Optimization (FO) owns and operates OR/ML and simulation systems that continually optimize the distribution of tens of millions of products across Amazon’s warehouses in the most cost-effective manner, utilizing large scale optimization techniques and distributed computing in trying to reduce overall transportation costs while improving the customer experience. We are focused on saving hundreds of millions of dollars using Optimization, machine learning, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply. We’re looking for a passionate, results-oriented, and inventive scientist who can create and improve models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative models for solving complex business problems in the area of outbound transportation planning and execution systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create optimization solutions to solve those problems at scale. You will directly impact our direct customers, and even play with big data and incredible scale in the background.

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 a Senior 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.

Are you excited by the idea of developing algorithms to improve the shopping experience for Amazon customers? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art modeling techniques? Join us and you'll help make the shopping experience better for millions of customers while also advancing the state of Amazon's science through publishing research! Key job responsibilities - Develop and apply new machine learning algorithms - Use expertise in supervised learning and causal inference to improve ML performance - Scale optimization techniques to drive business value - Design A/B tests and conduct statistical analysis on their results - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers - Present and publish science research, contributing to Amazon's science community - Mentor junior engineers and scientists. - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area About the team Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.

External job description As a Sr. Applied Scientist, you will be responsible for assessing and optimizing the performance and reliability of our new and emerging category of devices – Kuiper Customer Terminal. Project Kuiper is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to un-served and under-served communities around the world. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: - Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes - Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks - Establishing scalable, efficient, automated processes to handle large scale design and data analysis - Conducting research into use conditions, materials and analysis techniques - Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis - Developing, implementing guidelines to continually optimize design processes - Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design - Using of programming languages like Python and Matlab for analytical/statistical analyses and automation - Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials - Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation - Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques