Careers

As a Data Scientist in Alexa Connections, you will lead the end-to-end development of machine learning and data science solutions that power intelligent communication experiences across channels such as calling, messaging and email. You will partner closely with product, engineering, and business leaders to translate ambiguous problems into scalable ML models, experimentation frameworks, and data-driven product decisions. In this role, you will design and deploy advanced ML and statistical models for capabilities such as prioritization, intent detection, and proactive action recommendations. You will analyze large-scale datasets and run rigorous experiments, including A/B testing and causal analysis, to measure impact and continuously improve customer engagement and product performance. Additionally, you will shape the applied science roadmap and collaborate with global cross-functional teams to deliver AI-driven solutions that scale to millions of Alexa customers. Key job responsibilities - Partner with product, engineering, operations, and security teams to translate complex business problems into scalable, production-ready data science and ML solutions. - Own the full lifecycle of model development, including exploratory analysis, model design, deployment, monitoring, and continuous improvement. - Define and track success metrics, conduct rigorous analyses, and provide insights that guide product launches, feature improvements, and data-driven decision-making. - Build data-driven business cases to prioritize science initiatives and demonstrate measurable impact of ML solutions. - Develop ML-powered systems supporting key business areas. - Lead research and analysis to understand customer interactions with Alexa, and enhance overall customer experience. - Contribute to the broader science community by mentoring analysts, improving data workflows and tooling, and publishing technical work in internal and external forums. A day in the life • Deep dive into our business metrics, analyze data, trends, and reviewing dashboards • Writing code: building packages in Python, writing SQL queries, deploying solutions for Connections experience teams to consume. • Leading or joining working sessions with Product Managers to refine problem statements new initiatives. • Exploring new features and model architectures, leveraging AWS services, documentation, and upskilling yourself to the latest technologies. • Leverage pre-trained LLMs to build applications that solve business problems for Connections experiences. • Meet with Sr. Engineers/Principal Engineers to align on solution designs. • Own or co-own MBR, WBR documents that are reviewed with Connections leadership team.

The science team within Amazon’s Manager Experience org (AMX) 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 an economist with expertise in applying causal inference methods, especially experimental design to topics in labor, personnel, education, or behavioral economics. We are particularly interested in candidates with experience applying these skills to strategic problems with significant business and/or social policy impact. The candidate will work with economists and engineers to estimate and validate their models on large scale data, and will help business partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business and its workforce. We are looking for a creative thinker who can combine a strong economic toolbox with a desire to learn from others, and who knows how to execute and deliver on big ideas. Ideal candidates will own key inputs to all stages of research projects, including model development, survey administration, experimental design, and data analysis. They will be customer-centric, working closely with business partners to define key research questions, communicate scientific approaches and findings, listen to and incorporate partner feedback, and deliver successful solutions.

Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of Ka band and S/C band communication payload and ground terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology with few legacy constraints. The team develops and designs the communication system of Amazon Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced L1/L2 proof of concept HW/SW systems to improve the performance and reliability of the Amazon Leo network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the design, integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities • Design advanced L1/L2 algorithms and solutions for the Amazon Leo communication system, particularly Multi-User MIMO techniques. • Develop proof-of-concepts for critical communication payload components using SDR platforms consisting of FPGAs and general-purpose processors. • Work with ASIC development teams to build power/area efficient L1/L2 HW accelerators to be integrated into Amazon Leo SoCs. • Provide specifications and work with implementation teams on the development of embedded L1/L2 HW/SW architectures. • Work with multi-disciplinary teams to develop advanced solutions for time, frequency and spatial acquisition/tracking in LEO systems, particularly under large uncertainties. • Develop link-level and system-level simulators and work closely with implementation teams to evaluate expected performance and provide quick feedback on potential improvements. • Develop testbeds consisting of digital, IF and RF components while accounting for link-budgets and RF/IF line-ups. Previous experiences with VSAs/VSGs, channel emulators, antennas (particularly phased-arrays) and anechoic chamber instrumentation are a plus. • Work with development teams on system integration and debugging from PHY to network layer, including interfacing with flight computer and SDN control subsystems. • Willing to work in fast-paced environment and take ownership that goes from algorithm specification, to HW/SW architecture definition, to proof-of-concept development, to testbed bring-up, to integration into the Amazon Leo system. • Be a team player and provide support when requested while being able to unblock themselves by reaching out to RF, ASIC, SW, Comsys and Testbed supporting teams to move forward in development, testing and integration activities. • Ability to adapt design and test activities based on current HW/SW capabilities delivered by the development teams.

Project Leo (former Kuiper) is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of Ka band and FR1 band communication payload and customer terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology at global scale. The team develops and designs the communication system for project Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced physical layer + protocol stacks systems as proof of concept and reference implementation to improve the performance and reliability of the LEO network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their causal inference and/or structural econometrics skillsets to solve real world problems. The intern will work in the area of Economics Intelligence in Amazon Returns and Recommerce Technology and Innovation and develop new, data-driven solutions to support the most critical components of this rapidly scaling team. Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. About the team The WWRR Economics Intelligence (RREI) team brings together Economists, Data Scientists, and Business Intelligence Engineers experts to delivers economic solutions focused on forecasting, causality, attribution, customer behavior for returns, recommerce, and sustainability domains.

Amazon Ads is a multi-billion dollar global business that delivers advertising experiences across Amazon's owned-and-operated properties (including Prime Video, Twitch, Fire TV, and Amazon.com), third-party publisher networks, and emerging channels like generative AI-powered shopping experiences. As one of the fastest-growing segments of Amazon, we operate at unprecedented scale across desktop, mobile, connected TV, and emerging surfaces. Within Amazon Ads, Traffic Quality is a critical pillar of advertiser trust and marketplace integrity. Our mission is to build advanced capabilities that work at petabyte scale to detect sophisticated invalid traffic (IVT) which includes sophisticated non-human traffic, bot networks, and fraudulent engagement patterns across programmatic advertising. We are on a journey to establish Amazon Ads as an industry leader in traffic quality standards and transparency. Our research agenda focuses on staying ahead of adversarial actors through continuous innovation in detection methodologies, leveraging state-of-the-art techniques in deep learning and generative modeling, user behavior and multi-modal representation learning, anomaly detection, time-series analysis, and sparse labeling methods. We process billions of ad events daily, developing novel algorithms that balance precision and recall while operating under strict latency constraints. Our work directly protects hundreds of millions of dollars in advertiser spend annually while maintaining a seamless user experience. Key job responsibilities Strategic Leadership & Vision - Define long-term science vision for Traffic Quality driven by advertiser and publisher needs, translating direction into actionable team plans. - Lead teams solving strategically important business problems independently, delivering robust, scalable scientific solutions with limited guidance. - Proactively identify technology gaps and business opportunities, determining resource allocation priorities. Scientific Innovation & Execution - Design and implement statistical and machine learning solutions to detect robotic and human traffic patterns across billions of daily ad events. - Own full development cycle for production-level code handling billions of ad requests: design, prototype, A/B testing, and deployment. - Hold team to highest scientific standards, reviewing modeling decisions and evaluating proposals for strengths and weaknesses. - Make sophisticated trade-offs balancing precision and recall under strict latency constraints. - Scope projects, design experiments, and improve methodologies for new data sources and model enhancements. - Stay current with scientific advancements and build publication strategy while championing excellence best practices. Operational Excellence & Customer Trust - Maintain advertiser trust through near real-time monitoring systems, responding rapidly to anomalies and metric deviations. - Ensure operational excellence through proactive quality signal investigation, root cause analysis, and swift remediation. - Directly protect hundreds of millions of dollars in advertiser spend annually while maintaining seamless user experience. Collaboration & Team Development - Partner with engineers, product managers, and cross-functional teams to solve complex IVT detection problems and influence strategic initiatives. - Hire, manage, coach, and promote scientists while building succession plans and growing future leaders. - Structure teams sustainably to meet scientific, business, and technology needs while fostering innovation culture. About the team Here are a few papers published by the team: 1/ [Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD 2023.](https://assets.amazon.science/b7/42/03be071743d5a57cb1656e6caa34/scaling-generative-pre-training-for-user-ad-activity-sequences.pdf) 2/ [SLIDR: Real-time Robot Detection On Online Ads, IAAI 2023, Deployed Highly Innovative Applications of AI Track (AAAI 2023)](https://assets.amazon.science/75/2f/3b7106b143f38f7f4d2806388ace/real-time-detection-of-robotic-traffic-in-online-advertising.pdf) 3/ [Self-supervised Representation Learning Across Sequential and Tabular Features Using Transformers, NeurIPS 2022, First Table Representation Learning Workshop](https://openreview.net/forum?id=wIIJlmr1Dsk)

Ready to Transform Amazon's Procurement Systems? Are you passionate about building scalable solutions that impact how Amazonians get their work done? Join us in revolutionizing Amazon's procurement technology landscape through advanced analytics and machine learning. We're seeking a talented Data Scientist to help build the next generation of procurement applications from the ground up. This is your opportunity to work on high-impact systems that combine advanced search capabilities, AI-powered assistance. About This Role As a Data Scientist in the Global Corporate Procurement (GCP) Tech team, you'll be instrumental in building modern, AI/ML-powered applications that transform Amazon's procurement systems. You'll work on a greenfield initiative to create innovative solutions leveraging machine learning, natural language processing, and predictive analytics that make procurement faster, smarter, and more intuitive for Amazonians worldwide. This role offers the unique opportunity to develop data-driven systems leveraging AI/ML services, modern statistical modeling techniques, and generative AI capabilities. You'll collaborate with experienced data scientists, engineers, and cross-functional partners to deliver solutions that will eventually serve Amazon's global workforce. What You'll Do You'll design, develop, and deploy scalable machine learning models and data pipelines that power Amazon's procurement ecosystem. Working in an agile environment, you'll take ownership of analytical solutions from conception through production deployment, contributing to technical decisions alongside experienced data scientists and engineers. Your work will directly impact the daily experience of Amazonians as they procure goods and services. Through collaboration with product managers, UX designers, and fellow data scientists, you'll translate complex business requirements into elegant data-driven solutions using advanced analytics, NLP, and AI/ML techniques. Key job responsibilities * Use data analyses and statistical techniques to develop solutions to improve customer experience and to guide business decision making * Identify predictors and causes of business-related problems and implement novel approaches related to forecasting and prediction * Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations * Collaborate with multiple teams as a leader of quantitative analysis and where you develop solutions that utilize the highest standards of analytical rigor and data integrity * Analyze and solve business problems at their root

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.

Are you interested in recommendation systems that deliver the most enjoyable content to millions of customers? Do you want to invent new ways to seamlessly connect Kids and Parents through books, videos, apps, and more across a growing number of devices? If that sounds like you, then come join the Amazon Kids+ Personalization team! Join a team on a mission to make Kids+ every child's favorite destination to independently create, explore, and learn — and give parents the confidence to let them. Learn more at http://www.amazon.com/kids. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers (SDEs, DEs). You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team We're a team of experienced engineers and builders who are genuinely passionate about what we make — and who we make it for. Many of us are parents ourselves, and all of us share a deep belief that kids deserve technology that's both safe and genuinely fun. That tension — between delight and trust, between independence and guardrails — is the creative challenge that gets us out of bed in the morning.

The Returns and Recommerce Economics & Intelligence team advances returns science to maximize efficiency in returns processes while enhancing customer experience. We bring together economists, analysts, and engineers who leverage methodologies including timeseries econometrics, structural modeling, machine learning, and data science to deliver actionable insights. Our work spans the entire returns value chain – from understanding customer behavior to optimizing recommerce strategies or warehouse operations. We are looking for detail-oriented, organized, and responsible individuals who are eager to learn how to apply their timeseries and macro-econometrics skillsets to solve real world problems. The intern will work in Returns and Recommerce Economics developing macro models to assess impacts of macro shocks on customer returns. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. These are full-time positions at 40 hours per week, with compensation being awarded on an hourly basis. Key job responsibilities Our PhD Economist Internship Program offers hands-on experience in applied economics, supported by mentorship, structured feedback, and professional development. Interns work on real business and research problems, building skills that prepare them for full-time economist roles at Amazon and beyond. You will learn how to build data sets and perform applied econometric analysis collaborating with economists, scientists, and product managers. These skills will translate well into writing applied chapters in your dissertation and provide you with work experience that may help you with placement. A day in the life