Careers

Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Sr Applied Scientist, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON ADVERTISING LLC Offered Position: Data Scientist II Job Location: New York, New York Job Number: AMZ9658237 Position Responsibilities: 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 $169,541/year to $207,500/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000

Who are we? Do you want to build Amazon's next $100B business? We're not just joining the shipping industry—we're transforming how billions of packages move across the world every year. Through evolving Amazon's controlled, predictable fulfillment network into a dynamic, adaptive shipping powerhouse we are building an intelligent system that optimizes in real-time to deliver on the promises businesses make to their customers. Our mission goes beyond moving boxes—we're spinning a flywheel where every new package makes our network stronger, faster, and more efficient. As we increase density and scale, we're revolutionizing shipping for businesses while simultaneously strengthening Amazon's own delivery capabilities, driving down costs and increasing speed for our entire ecosystem. What will you do? Amazon shipping is seeking a Senior Data Scientist with strong pricing and machine learning skills to work in an embedded team, partnering closely with commercial, product and tech. This person will be responsible for developing demand prediction models for Amazon shipping’s spot pricing system. As a Senior Data Scientist, you will be part of a science team responsible for improving price discovery across Amazon shipping, measuring the impact of model implementation, and defining a roadmap for improvements and expansion of the models into new unique use cases. This person will be collaborating closely with business and software teams to research, innovate, and solve high impact economics problems facing the worldwide Amazon shipping business. Who are you? The ideal candidate is analytical, resourceful, curious and team oriented, with clear communication skills and the ability to build strong relationships with key stakeholders. You should be a strong owner, are right a lot, and have a proven track record of taking on end-to-end ownership of and successfully delivering complex projects in a fast-paced and dynamic business environment. As this position involves regular interaction with senior leadership (director+), you need to be comfortable communicating at that level while also working directly with various functional teams. Key job responsibilities * Combine ML methodologies with fundamental economics principles to create new pricing algorithms. * Automate price exploration through automated experimentation methodologies, for example using multi-armed bandit strategies. * Partner with other scientists to dynamically predict prices to maximize capacity utilization. * Collaborate with product managers, data scientists, and software developers to incorporate models into production processes and influence senior leaders. * Educate non-technical business leaders on complex modeling concepts, and explain modeling results, implications, and performance in an accessible manner. * Independently identify and pursue new opportunities to leverage economic insights * Opportunity to expand into other domains such as causal analytics, optimization and simulation. About the team Amazon Shipping's pricing team empowers our global business to find strategic harmony between growth and profit tradeoffs, while seeking long term customer value and financial viability. Our people and systems help identify and drive synergy between demand, operational, and economic planning. The breadth of our problems range from CEO-level strategic support to in-depth mathematical experimentation and optimization. Excited by the intersection of data and large scale strategic decision-making? This is the team for you!

Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. The Sr. Applied Scientist Pricing Optimization, Leo Global Pricing Strategy will have an outsized impact on the profitability of Amazon Leo directly through building the initial foundational models to enable the business to optimize our pricing and product feature strategies. You will be building a true "0 to 1" function, powering the science behind pricing decisions and driving science automation at a global scale. 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. A day in the life You will design, develop, and deploy advanced machine‑learning models to predict customer‑level behavior (revenue, churn, usage, migration, product choice) and response to pricing changes. You will build robust models that capture the complexities of multi‑product bundling interactions in a subscription business model and regional nuances in supply/demand and consumer choice alternative choices. You will implement scalable inference systems, will monitor model performance, and will automate retraining. Collaboration with cross‑functional teams will be critical to ensure that technical solutions will align with business objectives and actionable strategies. Establishing mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques will be critical.

The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. The Search Relevance team focuses on several technical areas for improving search quality. In this role, you will invent universally applicable signals and algorithms for training machine-learned ranking models. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products. You will work on problems such as predicting the popularity of new products, developing new ranking features and algorithms that capture unique characteristics, and analyzing the differences in behavior of different categories of customers. The work will span the whole development pipeline, including data analysis, prototyping, A/B testing, and creating production-level components. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world’s leading Internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California. Please visit https://www.amazon.science for more information

Amazon Business (AB) is a USD35B+ business spanning 10 countries (US, Germany, UK, France, Italy, Spain, Japan, Canada, India and Mexico). Amazon Business (amazon.in/business) launched in India in September 2017 with the vision to be the destination for all businesses in India to find, discover and buy for all their business needs, and it is still day 1 for us. Amazon Business represents an incredible opportunity to address a vast new market segment and customer base and is an area of high interest for Amazon. We are focused on building solutions that enable the B2B customer to find, research, and buy products and services from a vast selection, across multiple devices, marketplaces and regions. India's B2B market represents a ~$110B annual opportunity of indirect spends across 63MM businesses including individual professionals, small businesses to large institutions (and everything in between). Our business customers have different needs than the traditional Amazon customer and we are reinventing everything from how we display our selection, how sellers price their products, and how we provide the right customer experience. We aim to make B2B procurement as seamless as consumer shopping by solving unique enterprise needs in vendor management, pricing, payments, and procurement workflows. As a Data Scientist you will investigate business problems using data, invent novel solutions and prototypes, and directly contribute to bringing your ideas to life through production implementation. Sample areas include but are not limited to: making customer acquisitions more efficient through different channels (search, socials), running personalisation initiatives for B2B customers to decide on high value actions such as credit, discounts etc, enabling more customers to access credit basis their online and offline history, identification of high-trust customers. Key job responsibilities - Partner with business stakeholders to deeply understand AB business problems and frame ambiguous business problems as science problems and solutions. - Perform data analysis and build data pipelines to drive business decisions. - Invent novel science solutions, develop prototypes, and deploy production software to solve business problems. - Review and guide science solutions across the team. - Publish and socialize your and the team's research across Amazon and external avenues as appropriate - Leverage industry best practices to establish repeatable applied science practices, principles & processes.

Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match! Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience. The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist. Key job responsibilities - You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product. - You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns. - You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders. - You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders. - You thrive in an agile and fast-paced environment on highly visible projects and initiatives.

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist III Job Location: Seattle, Washington Job Number: AMZ9674365 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy. Position Requirements: Master's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $162,752/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

We are seeking an Applied Scientist for our Device Ad Products science team. This team addresses challenging optimization problems related to how advertisements are priced, selected, allocated and shown to customers on Amazon devices including Fire TV, Alexa and Fire Tablet. As Applied Scientist, you will be responsible for improving advertising performance and delivering innovative advertising experiences for display and video ads on Amazon Devices. This team leads initiatives to improve advertising fundamentals such as relevance, coverage, CTR, and CPSU (cost per sign up for streaming services) which in turn increase advertising revenue across Amazon's devices worldwide. You will own the scoping, implementation, and launch of science based ad solutions and experiences specifically for these entertainment focused environments. Key job responsibilities - Gain a comprehensive understanding of the customer lifecycle journey with Amazon Ads, and develop sophisticated models to optimize various conversion KPIs for enhanced marketing effectiveness. - Develop scalable data processing pipelines and architectures to ingest, transform, and enrich Customer data from various sources (Retail, Prime Video, FireTV and AppStore). - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with product managers and engineers to launch your models to customers. - Drive innovation within your team and partner closely with other scientists, engineers and Product Managers to build science roadmaps - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, multi-modal learning and related fields, and identify opportunities to apply them to Advertising Use Cases. - We are looking for world class researchers with experience in one or more of the following areas of Agentic AI for ads targeting - autonomous agents, multi agent orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. - Effectively communicate complex science problems and solutions to both technical and non-technical audiences. A day in the life In this role, you will regularly work with scientists and technical leaders across the advertising organization, including other science teams, product management, and senior leadership. You will also collaborate with science leaders across Amazon Devices and Prime Video organizations to build company-wide alignment. You will manage and work closely alongside your team of applied and data scientists to guide them through high-ambiguity problems and deliver robust, scalable solutions. About the team This role is on Device Ads and Personalization (DAPP) team, which is under Amazon Publisher Monetization (APM). This team has a vision to create innovative Ad experiences on Amazon Devices, providing customers better convenience and more selection.