Careers

AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing? Amazon Web Services is looking for a highly motivated, Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals. We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities - Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. - Proficiency in both Supervised(Linear/Logistic Regression) and UnSupervised algorithms(k means clustering, Principle Component Analysis, Market Basket analysis). - Experience in solving optimization problems like inventory and network optimization . Should have hands on experience in Linear Programming. - Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area - Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. - Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions - Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Are you a MS or PhD student interested in a 2025 Internship in the field of machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create 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. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain, UAE, and UK). Please note these are not remote internships.

We're a research team assisting thousands of AWS sales reps to be their most productive and helpful selves. We work with sales, operations, and finance teams to guide strategic and tactical investment decisions across every part of the sales cycle. Key job responsibilities Your key responsibilities are meeting customers, understanding their needs, designing models to meet those needs, and then writing the code to gather and analyze the necessary data. About the team We're part of a large science and economics team embedded in AWS's sales org. We build models to influence large scale investment decisions and operations - everything from annual planning, to training and compensation, to customer level recommendations. We are fortunate enough to have data and PM support so that we can spend more time with our customers (and building models to help them). About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices.

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

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 protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team. The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation. Please visit https://www.amazon.science for more information

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us! The Supply Chain Optimization Technologies (SCOT) group is seeking a Principal Research Scientist to join our Optimal Sourcing Systems team. The Optimal Sourcing Systems (OSS) owns the optimization of inventory sourcing and the orchestration of inbound flows from vendors worldwide. We source inventory from thousands of vendors for millions of products globally while orchestrating the inbound flow for billions of units. Our goals are to increase access to supply for speed and placement, improve supply chain-driven vendor experience, and reduce end-to-end supply chain costs, all in service of maximizing Long-Term Free Cash Flow (LTFCF) for Amazon. Your tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long term profitability. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities - Design, implement and evaluate models, agents and software prototypes - Technical leadership for a group of highly motivated and talented scientists - Influence team business and engineering strategies - Work closely with partner teams to develop solutions to ambiguous business problems and integrate novel methodology into our team and business - Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community - Raise the bar of scientific research by innovating and publishing - Exercise sound judgment to prioritize between short-term vs. long-term and business vs. technology needs. - Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives. A day in the life In this role, you will have opportunity to work with partners and stakeholders from Amazon’s retail, seller and operation departments worldwide. You will understand their challenges and pain points, and help develop solutions that improve how Amazon source inventory and enable world class vendor experiences. To implement your solutions, you will work closely with our product and engineering teams. Your work will have high visibility and impacts to Amazon’s business operation. About the team Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies

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.

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