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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!

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop computer vision models on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: - Exploring the data and brainstorming and prioritizing ideas for model development - Implementing new features in our sizable code base - Training models in support of experimental or performance goals - T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work on the classified networks. Three to four days a week, you would travel to the customer site in Northern Virginia to perform tasking as described below. Weekdays when you do not travel to the customer site, you would work from your local Amazon office. You would work collaboratively with teammates to use and contribute to a well-maintained code base that the team has developed over the last several years, almost entirely in python. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, Apache AirFlow, GitLab, and Visual Studio Code. We are a very collaborative team, and regularly teach and learn from each other, so, if you are familiar with some of these technologies, but unfamiliar with others, we encourage you to apply - especially if you are someone who likes to learn. We are always learning on the job ourselves. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to develop computer vision models on overhead imagery: - Run data conversion pipelines to transform customer data into the structure needed by models for training - Perform EDA on the customer data - Train deep neural network models on overhead imagery - Develop and implement hyper-parameter optimization strategies - Test and Evaluate models and analyze results - Package and deliver models to the customer - Incorporate model R&D from low-side researchers - Implement new features to the model development code base - Collaborate with the rest of the team on long term strategy and short-medium term implementation. - Contribute to presentations to the customer regarding the team’s work.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop vision language models (VLMs) on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: - Exploring the data and brainstorming and prioritizing ideas for model development - Implementing new features - Training models in support of experimental or performance goals - T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work on the classified networks. You would work collaboratively with teammates to develop and use a python codebase for fine-tuning VLMs. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, GitLab, and Visual Studio Code. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to fine-tune VLMs on overhead imagery: - Run data conversion pipelines to transform customer data into the structure needed by models for training - Perform EDA on the customer data - Train VLMs on overhead imagery - Develop and implement hyper-parameter optimization strategies - Test and Evaluate models and analyze results - Package and deliver models to the customer - Implement new features to the code base - Collaborate with the rest of the team on long term strategy and short-medium term implementation. - Contribute to presentations to the customer regarding the team’s work.

This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance. Join a sizeable team of data scientists, research scientists, and machine learning engineers that develop computer vision models on overhead imagery for a high-impact government customer. We own the entire machine learning development life cycle, developing models on customer data: Exploring the data and brainstorming and prioritizing ideas for model development Implementing new features in our sizable code base Training models in support of experimental or performance goals T&E-ing, packaging, and delivering models We perform this work on both unclassified and classified networks, with portions of our team working on each network. We seek a new team member to work primarily on the unclassified networks. You would work collaboratively with teammates to use and contribute to a well-maintained code base that the team has developed over the last several years, almost entirely in python. You would have great opportunities to learn from team members and technical leads, while also having opportunities for ownership of important project workflows. You would work with Jupyter Notebooks, the Linux command line, AWS Services, GitLab, and Visual Studio Code. We are a very collaborative team, and regularly teach and learn from each other, so, if you are familiar with some of these technologies, but unfamiliar with others, we encourage you to apply - especially if you are someone who likes to learn. We are always learning on the job ourselves. Key job responsibilities With support from technical leads, carry out tasking across the entire machine learning development lifecycle to develop computer vision models on overhead imagery: Run data conversion pipelines to transform customer data into the structure needed by models for training Perform EDA on the customer data Train deep neural network models on overhead imagery Develop and implement hyper-parameter optimization strategies Test and Evaluate models and analyze results Package and deliver models to the customer Implement new features to the model development code base Collaborate with the rest of the team on long term strategy and short-medium term implementation. Contribute to presentations to the customer regarding the team’s work.

As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, NLP, and LLMs to create reliable, scalable, high-performance products that raise the bar in operational excellence. Working closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver customer-impacting results through innovative AI solutions. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.

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

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!