Careers

Amazon’s FinOps Global Data Analytics’s (GDA) science team seeks an outstanding Data Scientist with the technical expertise and business intuition to invent the future of Accounts Receivable and Account Payable at Amazon. As a key member of the science team, the Data Scientist will own high-visibility analyses, methodology, and algorithms in the Order-to-Cash (O2C) and Procure-to-Pay lifecycles to drive free cash flow improvements for Amazon Finance Operations. This is a unique opportunity in a growing data science and economics team with a charter to optimize operations and planning with complex trade-offs between customer experience, credit risk, cash flow, and operational efficiencies. Key job responsibilities The Data Scientist's responsibilities include, but are not limited to the following points: - Extract and analyze large amounts of data from Order-to-Cash and Procure-to-Pay processes and associated business functions. - Adapt statistical and machine learning methodologies for Finance Operations by developing and testing models, running computational experiments, and fine-tuning model parameters. - Use computational methods to identify relationships between business data and outcomes, define outliers and anomalies, and justify those outcomes to business customers. - Communicate verbally and in writing to business customers with various levels of technical knowledge, educate stakeholders on our research and data science practice, and deliver actionable insights and recommendations - Develop code to analyze data (SQL, PySpark, Scala, etc.) and build statistical and machine learning models and algorithms (Python, R, Scala, etc.). - Collaborate with business and operational stakeholders and product managers to innovate on behalf of customers leveraging data science methodologies, and partner with engineers and scientists to design, develop, and scale machine learning models A day in the life As a successful data scientist in GDA’s Science team, you will dive deep on data from across Amazon's numerous businesses, extract new assets, drive investigations and algorithm development, and interface with technical and non-technical customers. You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of finance and operational processes into models, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future. The role will work in a genuinely global environment, across various functional teams; with daily interaction across India, US, and Europe. About the team Global Data Analytics (GDA) supports decisions in AR and AP. In close cooperation with our stakeholders, we agree and build uniform metrics; use data from a ‘single source of truth’; provide automated, self-service, standard reporting; and build predictive analytics. Our topmost ambition is to actively contribute to the improvement of Amazon's Free Cash Flow by value-adding analytics. Our success is built on users' trust in our data and the reliability of our analytics tools. GDA’s data scientists and economists further that mission with rigorous statistical, econometric, and ML models to compliment reporting and analysis developed by GDA’s analytical, BI, and Finance professionals.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities • Demonstrate proficiency in supervised algorithms (tree-based models, neural networks) and unsupervised algorithms (clustering). • Rapidly design, prototype, and test multiple hypotheses in a high-ambiguity environment, utilizing quantitative analysis and business judgment. • Report findings in a scientifically rigorous manner. • Collaborate with software engineers, product managers, and domain experts to identify and address challenges requiring innovative solutions for our products. • Acquire knowledge of Amazon's diverse data resources and determine when, how, and which resources to leverage or exclude. • Integrate successful experiments into large-scale, highly complex production services by collaborating with software engineering teams. • Maintain technical documentation and effectively communicate results to diverse audiences. • Evaluate trade-offs by considering complexity, long-term benefits, and the reusability of existing solution

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.

Amazon's EU International Technology (EU INTech) Selection Expansion (SelEx) charter mission is to accelerate the selection flywheel for Sellers. To achieve our mission, we drive bottoms-up innovations with the mental model of the EU first solution and scale WW. Our North Star is to delight Sellers with an automated selection expansion experience to help them grow their business, bringing their selection to all customers world-wide. Key job responsibilities We are looking for Applied Scientists who are passionate to solve highly ambiguous and challenging problems at global scale. You will be responsible for major science challenges for our team, including forecasting, ranking and reccomendations. You will design, develop, deliver and support a variety of models in collaboration with a variety of roles and partner teams around the world. You will influence scientific direction and best practices and maintain quality on team deliverables. A day in the life You will work with Sr and Principal PM-T, TPM, BIE and other APSCI (internal and external to the team) to create solutions/models that will help seller to maximize the value of their investments while expanding in EU and WW. You will be supported by a team of more than 25 engineers to build the next chapter of selection expansion. About the team We are builders focused in one of the most critical sections of the flywheel: Selection. We built and own solutions such as Exports Central and EEA (European Expansion Accelerator), and continue to evolve and create ways to bring selection around the world.

Amazon's Search Science and AI team creates ML algorithms that connect customers around the world with products that delight them. We harness cutting-edge ML at Amazon's scale to make the customer experience easier and smoother. Our impact is large. For example, if your innovations save even 1 minute per customer per year, then for every 100 million customers, you save approximately 190 years of human effort. Key job responsibilities You will build search ranking systems that work for thousands of product types, billions of queries, and hundreds of millions of customers spread around the world. As an Applied Scientist you will find the next set of big improvements to ranking, leverage large datasets to understand the complexities of customer behavior, and get your hands dirty by building ML models that work at Amazon scale. In addition to typical topics in ranking, we are particularly interested in exploration techniques and reinforcement learning. A day in the life Our primary focus is improving search ranking systems. On a day-to-day this means building ML models, analyzing data from your recent A/B tests, and guiding teams on best practices. You will also find yourself in meetings with business and tech leaders at Amazon communicating your next big initiative. About the team We are a team consisting of ML scientists and software engineers. Our interests and activities span machine learning for better ranking, statistics for better decision making, and infrastructure to make it all happen at scale and efficiently.

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. Key job responsibilities As an Applied Scientist with the AIT team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistance technology. You will leverage Amazon’s heterogeneous data sources, unique but diverse international customer nuances and large-scale computing resources to accelerate advances in voice domain in multi-modal setup. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to will tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. A day in the life · Analyze, understand, and model customer behavior and the customer experience based on large scale data. Especially showing passion towards solving for international customer-centric challenges. · Build novel online & offline evaluation metrics an methodologies for personal digital assistants and customer scenarios, on multi-modal devices. · innovate and deliver deep learning based innovation across life-cycle such as policy-based learning, international customer specific model performance tuning. · Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing · Contribute through industry first research to drive the innovation forward.

What does our Selection Monitoring do? Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we use machine learning and cluster-computing technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing . The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of information Extraction, Efficient crawling at internet scale. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including - Scale (build models to handle billions of pages), - Accuracy (extreme requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information information from world wide web - Intelligently cluster web pages, segment and classify regions , extract relevant information and structure the data available on semi-structured web pages - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities Job Responsibilities - Use AI, NLP and advances in LLMs/SLMs to create scalable solutions for business problems - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes - Design, develop, evaluate and deploy, innovative and highly scalable ML models - Work closely with software engineering teams to drive real-time model implementations - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance - Leading projects and mentoring other scientists, engineers in the use of ML techniques

As a Principal Applied Scientist, you are a trusted part of the technical leadership. 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. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. 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. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team We are the Shopping Discovery & Evaluation team, and our vision is to make Amazon the internet’s most trustworthy, helpful, and delightful guide for customers on any shopping mission. From the moment customers visit our store, we help them find what they are looking for and delight in our vast offering of products and services (Navigation Experience). We create immersive, visual, and personalized shopping experiences that inspire customers to kickstart their next shopping journey (Inspire, Amazon Native Player). We bring together trusted, authentic inputs from the community, and surface those inputs with the help of generative AI, to help customers confidently inform their next purchase (Community Feedback).

Are you passionate about AI for recommendation systems? Do you want to influence the content that customers see at Amazon.com? Our recommendation services team designs and implements scalable machine learning solutions to personalize and optimize customer experience across Amazon retail pages. We are currently expanding in New York, and are looking for an applied scientist to join us in this exciting journey. As an Applied Scientist, you will: - Push the boundaries of real-world ranking, recommendation, and optimization systems - Support science, engineering and product development on a scale only seen at Amazon. - Champion and define best practices to maximize learnings while mentoring more junior scientists and engineers. - Obsess over customer needs and satisfaction. - Create intellectual property, influence others while demonstrating significant creativity and being vocally self-critical. - Shape product definitions and objective and surface signals on how these objectives meet long term customer needs. - Translate metrics & signals into actionable plans to calibrate individual components. - Operate hands-on and as an implementor of algorithms and models delivered to production systems. - Help define customer focused research initiatives. Please visit https://www.amazon.science for more information.

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics