Careers

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team at Amazon is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for all Amazon programs. Come and join us! Amazon’s CBA team is looking for Economists, who can work at the intersection of economics, statistics and machine learning; and leverage the power of big data to solve complex problems like long-term causal effect estimation. Key job responsibilities Economists at Amazon are expected to work directly with other Economists and senior management on key business problems in retail, international retail, cloud computing, third party merchants, search, Kindle, streaming video, and operations. Amazon economists will apply the frontier of economic thinking to market design, pricing, forecasting, program evaluation, online advertising and other areas. You will build econometric models, using our world class data systems, and apply economic theory to solve business problems in a fast moving environment. Economists at Amazon will be expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to catch bad actors, build ML models and solve complex problems. If so, working on the Loss Prevention Tech team as a Sr Applied Scientist is the place for you! We detect theft, fraud and organized crime happening across our global supply chain and operations for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the cost savings of Amazon's inventory losses. The primary role of a Sr Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on all the fraud investigations happening across Amazon operations. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in ( Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of building fraud detections, detecting organized crime and the ability to use data and research to make changes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Key job responsibilities - Own KPIs that measure fraud management performance and efficiencies. - Detect and automate theft, fraud MOs - Detect organized crime rings and bad actor clusters - Build data or computer vision based ML models - Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational). - Contribute to the overall fraud management and product development strategies. - Present key learnings and vision to stakeholders and leadership. - Integrate ML detection models via software applications About the team We believe that building a culture that is welcoming and inclusive is integral to people doing their best work and is essential to what we can achieve as a company. We actively recruit people from diverse backgrounds to build a supportive and inclusive workplace. Our team puts a high value on work-live balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

The Amazon Last Mile Flex Delivery Planning Science team is looking for an L5-L6 Research Scientist or Applied Scientist with strong skills in Optimization/Operations Research. Flex is Amazon's gig economy platform for procuring drivers to satisfy the overflow demand from AMZL, as well as specialty deliveries like Sub-same Day Deliveries (SSD) and groceries (GSF). Like Uber, drivers download the Flex app and click on offers of work time blocks, during which they are paid to execute deliveries from a particular warehouse, over a particular time window. Unlike Uber, we allow drivers to schedule work up to a week in advance. Challenges involve scheduling drivers over time, in the presence of long lead-times, uncertainties in both demand and supply, while minimizing cost and the risks of late deliveries or excess drivers. We are also working on the integration of our driver scheduling systems with capacity planning, routing & assignment, dynamic pricing, smart offer targeting, and long-term value. We are looking for candidates with strong skills in Optimization modeling (Mixed Integer Programming, Dynamic Programming, Decomposition Methods), as well as solid skills in Python coding and data collection and analysis. Some background in Control Theory, Machine Learning, and Economics would be helpful too. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment and a desire to help shape the overall business. Key job responsibilities • Design and develop advanced mathematical, optimization models and apply them to define strategic and tactical needs and drive the appropriate business and technical solutions in the areas of delivery planning, supply chain optimization, network optimization, economics, and control theory. • Apply mathematical optimization and control techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming, decomposition methods, model predictive control) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software. • Research, prototype, simulate, and experiment with these models by using modeling languages such as Python, MATLAB, Mosel or R; participate in the production level deployment. • Create, enhance, and maintain technical documentation • Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders. • Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans. • Influence organization's long-term roadmap and resourcing, onboard new technologies onto Science team's toolbox, mentor other Scientists. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA

职位：Applied scientist 应用科学家实习生 毕业时间：2024年10月 - 2025年9月之间毕业的应届毕业生 · 入职日期：2024年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续3个月 · 工作地点：北京朝阳区酒仙桥路恒通商务园区 · 校招信息请参考校园招聘申请手册： https://amazonexteu.qualtrics.com/CP/File.php?F=F_55YI0e7rNdeoB6e 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。 如果您正在攻读NLP，IR或搜索领域专业的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品，并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索NLP和IR领域的创新，基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务，通过数据，建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。 We are open to hiring candidates to work out of one of the following locations: Beijing, 11, CHN

We’re seeking a thought leader to direct Advanced ML initiatives aimed at scaling our $600B+ Amazon ecommerce business. This person will also be a deep learning practitioner/thinker and guide the research in these areas. They’ll have the ability to drive cutting edge, product-oriented research and should have a notable publication record. This intellectual thought leader will help enhance the science in addition to developing the thinking of our team. This leader will build / develop the team, direct and shape the science philosophy, and plan / strategize, as we explore domains such as reinforcement learning (RL), optimization, simulation, and leading technology in Large Language Models (LLMs) to facilitate seller recruiting, onboarding, growth, and brand building. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon [Earth's most customer-centric internet company]. About the team Selling Partner Recruitment and Success (SPRS) builds the programs, tools, systems, and science to recruit new selling partners with valuable selection into Amazon’s stores, drive their engagement with Amazon’s selling programs and services, and empower them to realize their potential for success and sustainable growth in our stores. We use advanced ML techniques to help scale the growth and success of sellers, who contribute over 60% of the sales for Amazon’s e-commerce business. The application of ML in this area is a relatively new focus for our business, and the opportunity is huge! We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Want to work on one of the highest priorities across Amazon Ads? This is your chance to help build a billion dollar business, innovate on a new product, and have a positive impact on millions of views while working with industry-leading technologies. We're growing a team to support the Sponsored Ads business that powers the advertising experience for millions of viewers and advertisers daily. This is a unique opportunity to get in early and drive significant portions of the technical roadmap. Amazon is investing heavily in building a world-class advertising business and developing a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses for driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are constantly challenging ourselves to create world-class products and an unparalleled shopping experience for our hundreds of millions of customers worldwide. We are building a suite of new services to enable a pioneering advertising initiative, Sponsored TV, using content-rich video optimized for mobile, desktop, and over-the-top platforms. This is a greenfield project in which you will to help define every aspect of the user experience, video services, content delivery, asset management, and advertiser self-service experience. Key job responsibilities - Be a thought leader and forward thinker, anticipating obstacles to success, helping avoid common failure modes, and holding us to a high standard of technical rigor and excellence in machine learning (ML). - Own and drive the most complex and strategic solutions across the business; responsible for many millions in revenue. - Define evaluation methods and metrics that measures viewer experience (e.g., ad relevance) and invent scientifically sound and scalable solutions in the streaming TV context, to improve viewer experience. - Seek to understand in depth the Sponsored TV offering and identify opportunities to grow our business via principled ML solutions. - Research, build, and deploy innovative ML solutions; working across all technical disciplines. - Identify untapped, high-risk technical and scientific directions, and stimulate new research directions that you will deliver on. - Be responsible for communicating our ML innovations to the broader internal & external scientific communities. - Hire, mentor, and guide senior scientists. - Partner with engineering leaders to build efficient and scalable solutions. About the team Sponsored TV Ads is a strategic new Amazon Ads product that is pioneering new experiences to help brands connect with millions of viewers. We are innovating on performance ads on TV. If you’re interested in joining a new and rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. We also strive to be a diverse and inclusive team and value work life balance. #SponsoredTV #STJobs We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

At Amazon, a large portion of our business is driven by third-party Sellers who set their own prices, and run their own promotions. The Pricing team is seeking a Sr. Applied Scientist to use statistical and machine learning techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems, helping Sellers offer Customers great prices, deals and promotions. The Applied Scientist will apply advanced techniques like Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTMs), CNNs and Transformers to develop robust price and deal forecasting models. Proficiency in Python, TensorFlow, or PyTorch is essential, with a strong understanding of deep learning techniques. Experience in forecasting domains such as finance, weather, or demand planning is highly valued. Join us in revolutionizing forecasting methods and driving actionable insights for our customers and sellers. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA

The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Seattle, WA, USA

This role is available across multiple locations in Spain (Barcelona, Madrid). Amazon Internships have start dates throughout the year and can vary in length from 3-6 months for full-time. Please note these are not remote internships. Are you a MS or PhD student interested in a 2024 Internship in the field of Applied Sciences? Are you interested in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? If so, we want to hear from you! We are looking for scientists with interest in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. 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. For more information on the Amazon Science community please visit the Science hub page: https://www.amazon.science/ If you’re interested in hearing more or have questions about Amazon Science internships, please feel free to join us for one of our upcoming informational sessions which you can sign up for via the ‘Events Calendar’ in our EMEA Science Intern landing page; https://amazonscienceopportunities.splashthat.com/ 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 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. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems We are open to hiring candidates to work out of one of the following locations: Barcelona, B, ESP | Madrid, M, ESP