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The candidate in this role will own delivery of science products and solutions to help Amazon Devices Sales and Marketing org. make better decisions: product recommendations to customers, segmentation, financial incrementality of marketing initiatives, A/B testing etc. Key job responsibilities The Amazon Devices organization designs, produces and markets Echo Speakers, Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players, Ring and Blink Smart Home & Security products. We are constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving customer experience on existing platforms. The Devices Data Services (DDS) team provides Data Science, Analytics and Engineering support to the broader organization to enable Sales and Marketing activities across all these product lines. We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, and building predictive machine learning models. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams. In this role, you will be a technical expert with massive impact. You will take the lead on developing advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs. Key Performance Areas - Implement statistical or machine learning methods to solve specific business problems. - Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. - Directly contribute to development of modern automated recommendation systems - Build customer-facing reporting tools to provide insights and metrics to track model performance and explain variance - Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback A day in the life You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and productionalization. About the team We are a full stack science team that empowers product, marketing, and other business leaders to better understand customers who use Amazon devices, make decisions on product development or optimization, and measure the effectiveness of their efforts against our customer’s expectation. Our focus area is to build analytical frameworks that help the organization either access data, better understand the decisions customers are making and why, or assess customer satisfaction.

Amazon's Selling Partner Support Science team builds the measurement and AI systems that power how Amazon understands, diagnoses, and eliminates the root causes of support contacts. Our vision is a continuous, science-driven pipeline where LLM-powered classification, causal impact measurement, and multi-modal friction detection work together to identify why Selling Partners experience frictions and quantify which interventions resolve them. Our systems process tens of millions of cases, evaluate hundreds of initiatives annually, and directly inform investment decisions across the Selling Partner Services organization. We are seeking a world-class Applied Scientist to help define and build the next generation of our LLM and ML systems. You will partner with applied scientists and engineers to design and deploy production-grade NLP pipelines, multi-modal AI frameworks, and scalable classification systems at Amazon's scale, owning your problem space end-to-end, from formulating a scientific approach to shipping a system that 50+ business teams rely on to make better decisions for millions of Selling Partners. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Amazon's Selling Partner Support Science team builds the measurement and AI systems that power how Amazon understands, diagnoses, and eliminates the root causes of support contacts. Our vision is a continuous, science-driven pipeline where LLM-powered classification, causal impact measurement, and multi-modal friction detection work together to identify why Selling Partners experience frictions and quantify which interventions resolve them. Our systems process tens of millions of cases, evaluate hundreds of initiatives annually, and directly inform investment decisions across the Selling Partner Services organization.

Employer: Amazon Web Services, Inc. Position: Data Scientist II Location: Houston, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $136000 - $184000) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

Amazon Robotics Vulcan is a robotic stowing system that uses a robot arm with a custom end-of-arm tool to place customer items into fulfillment center storage bins, alongside human associates. We operate in live fulfillment centers today and are scaling to additional sites globally. The Vulcan Motion team owns the motion stack that makes every interaction between the robot and the bin safe, fast, and predictable: real-time force-controlled manipulation, motion planning for insert and retract behaviors, compliant contact behaviors, and the safety envelope around all of it. We have many areas that need experienced scientists to drive from prototype to deployment at a global scale. For example: the framework our team uses to design, benchmark, and select controllers for each contact-rich behavior; the long-term controller roadmap with our industrial robot-arm vendors; the functional-safety envelope for live deployment; and the recovery architecture the robot uses when unexpected contact occurs. You may own one or two of these arcs depending on team needs and your strengths. This is a hands-on technical leadership role. You will write production C++ and Python, review code, and hold the technical bar on real-time control design selections that affect every cycle the robot executes. You will lead collaborations between our team and external partner teams in vision, hardware, and operations. Key job responsibilities - Research, propose, architect, and deliver complex features such as unified contact-control frameworks, robot-arm integration roadmaps, functional-safety envelopes, and motion recovery architectures. - Bring recent scientific advances in force control, compliant manipulation, and sim-to-real transfer into production. - Lead significant architectural and strategic initiatives together with more junior teammates. - Work across cross-disciplinary teams (hardware, safety, operations, vendor engineering) to deliver novel, synergistic features and capabilities. - Stay current with recent advances in robotics control, manipulation, and industrial automation. - Own the technical bar on real-time control design decisions and serve as the senior technical interface to external robot-arm engineering teams. A day in the life 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 Motion is one of several teams inside Amazon Robotics Vulcan. We ship weekly to live fulfillment centers, operate a fast iteration loop with real production data, and work across the full motion stack, from real-time controllers on hardware up through mission-level motion planning. We are looking for a senior Applied Scientist to help drive the next generation of robot behaviors alongside a strong existing team. If you want to go deep on controls problems, stay hands-on with hardware, and contribute to architectural direction, this role is for you.

Are you a PhD interested in machine learning, natural language processing, computer vision, automated reasoning, robotics, or quantum technologies? We are looking for skilled scientists capable of putting theory into practice through experimentation and invention, leveraging science techniques and implementing systems to work on massive datasets in an effort to tackle never-before-solved problems. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Scientist, you will own the design and development of end-to-end systems. You’ll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Key job responsibilities Amazon Science gives insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists use our working backwards method to enrich the way we live and work. For more information on the Amazon Science community please visit https://www.amazon.science.

The Alexa AI AURORA organization is seeking a passionate, talented, and resourceful Senior Data Scientist to define and solve complex, ambiguous problems in state-of-the-art conversational AI. You will lead large-scale data science initiatives across the fields of Large Language Models (LLMs), Natural Language Processing (NLP), and Artificial Intelligence (AI), selecting the ideal methodologies from a wide range of data science disciplines to drive measurable business impact for millions of Alexa customers. In this role, you will autonomously define problem spaces and solution approaches, working closely with business, science, and engineering teams to build consensus and influence strategy. You will advise senior leadership on data-driven decisions, identify blind spots in existing metrics, and propose new measurements that shape our product direction. You will actively mentor and develop other data scientists while setting standards for scientific rigor and operational excellence within the team. The ideal candidate has broad expertise across multiple data science disciplines and a deep understanding of how software systems, data pipelines, and business processes interact. They take the lead on complex projects with minimal guidance, make sound trade-offs between short-term customer needs and long-term technical investments, and deliver solutions that are scalable, reproducible, and actionable. A proven track record of launching data science solutions that drive significant business outcomes is essential. Strong communication skills, the ability to document and present technical findings to both technical and non-technical audiences, and a commitment to collaborative teamwork are absolute requirements. Join us in shaping the future of Generative AI and delivering unparalleled experiences for Alexa customers worldwide. Key job responsibilities Define the data science strategy for conversation modelling, content generation, and automated quality assurance by evaluating a wide range of methodologies across machine learning, generative AI, and computer vision, recommending the right approach based on business needs and scientific rigor. Lead the design and end-to-end delivery of complex, ambiguous data science initiatives from problem formulation through experimentation to production deployment, autonomously defining the problem space, selecting ideal solution approaches, and driving measurable business outcomes. Make high-judgment trade-offs across audio, text, and visual quality dimensions, balancing short-term customer needs against long-term platform extensibility, cost efficiency, and scalability while quantifying the impact of each decision. Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, identifying blind spots in existing measurements and proposing new mechanisms that institutionalize rigorous validation across customer touch points. Identify new business opportunities by staying at the forefront of AI/ML advances, translating emerging techniques into actionable data science directions with clear, quantifiable customer and business impact. Drive consensus across multiple teams on the architectural and methodological decisions underlying scalable agentic systems for conversation understanding and generation, ensuring alignment between data, software systems, and business processes. Set and continuously raise the bar for data science best practices across the team, creating models and analyses that are actionable, reproducible, and easy for others to contribute to and extend. Tackle the team's most complex technical problems, applying broad expertise across multiple data science disciplines while maintaining practical focus on solution generalizability and customer value. Actively mentor and develop other data scientists in the organization, leading scientific reviews, providing constructive feedback on methodology and results, and keeping the team current on data science advancements. Advance the team's scientific reputation through high-impact publications and presentations at top-tier venues, and generate intellectual property through patents. About the team AURORA is the AI runtime backbone and horizontal intelligence team that powers Alexa's core infrastructure, AI capabilities, and specialized conversational models. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing science solutions that connect key conversational capabilities, and transforming how builders create at scale. We empower 1P and 3P engineers and scientists worldwide with modular, reusable platforms that accelerate innovation while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale.

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.

Amazon Leo is Amazon's low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Role As a Senior Applied Scientist in Project Leo, you’ll be leading us in making critical and time sensitive decisions that impact customers. You’ll use your machine learning expertise to build solutions that can scale and solve the business problem, and your engineering experience to build systems that take those solutions to production; it's an exciting opportunity to apply data science to help improve fraud detection accuracy, inference, and customer experience monitoring activity. It’s fast paced, data driven, and impactful. 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 The position requires hands-on expertise in Analytics to identify and isolate issues, Statistical Modeling and traditional Machine Learning, the ability to write queries to aid in data extraction, and the ability to productionalize models. This role is a self sufficient scientist that can source data, build and evaluate models, and ultimately take those models and rules to deployment. You should have excellent communication skills and be able to work with stakeholders at all levels. Above all you should be a passionate, hard-working and creative person who loves creating business impact, loves solving difficult problems and doesn’t mind getting involved in the details. A day in the life As part of the Amazon Leo Data Science Platform team, you will collaborate with a diverse group of internal stakeholders, including fraud operations, Engineering teams, and the Data Platform, to identify and address fraud vulnerabilities. You will have the opportunity to develop rules and ML models to prevent Customer Terminal (CT) usage fraud and abuse. Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. If you are passionate about working with large-scale data, we offer ample opportunities to do so. About the team The Amazon Leo Data Science Platform team builds services to ingest, transform, and aggregate data from various devices in Leo Network, and auto detect, diagnose, and resolve issues. We use ML technology to monitor customer experience and prevent fraud and abuse.

We are building the next generation of autonomous AI agents that enable Amazon customers to seamlessly discover and purchase products across the open web. Our systems operate in highly dynamic real-world environments, navigating thousands of third-party merchant experiences with production-grade reliability, scalability, and safety. This role sits at the intersection of Agentic AI, LLMs, reinforcement learning, multimodal reasoning, and large-scale distributed systems. As an Applied Scientist, you will help define the science and architecture powering internet-scale web agents and autonomous purchasing systems. In this role, you will: - Work on autonomous AI agents operating in open-world environments rather than static benchmarks. - Solve challenging research problems at the intersection of LLMs, web interaction, multimodal reasoning, and scalable systems. - Influence products that directly impact millions of Amazon customers. - Build systems that must generalize across thousands of constantly evolving third-party websites. - Partner closely with science, engineering, and product leaders to shape the future of AI-powered shopping experiences. - Have the opportunity to publish research, file patents, and contribute to Amazon-wide AI innovation. Key job responsibilities - Design scalable evaluation and benchmarking systems for autonomous agents operating in dynamic web environments. - Develop techniques for robust agent planning, error recovery, and adaptation under distribution shift. - Build multimodal AI systems that reason over screenshots, DOM structures, user intent, and interaction trajectories. - Lead scientific direction for agent reliability, task completion, and customer trust. - Mentor scientists and engineers on advanced AI methodologies and experimentation. About the team The Buy For Me purchasing team owns the mission of completing customer purchases on off-amazon sites through both deterministic protocols and agentic methods. This role is with the agentic purchase team which is comprised of both SDEs and Applied Scientists working closely on production agents and offline capabilities to explore off-amazon sites, validate purchasing quality and onboard new sites to the Buy For Me program.