Data Scientist

Who you are

• 2+ years of data scientist experience
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• 1+ years of guiding and coaching a group of researchers experience
• 1+ years of working with or evaluating AI systems experience
• 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
• Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
• Experience applying theoretical models in an applied environment
• Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
• Knowledge of machine learning concepts and their application to reasoning and problem-solving
• Experience in Python, Perl, or another scripting language
• Experience in a ML or data scientist role with a large technology company
• Experience in defining and creating benchmarks for assessing GenAI model performance
• Experience working on multi-team, cross-disciplinary projects
• Experience applying quantitative analysis to solve business problems and making data-driven business decisions
• Experience effectively communicating complex concepts through written and verbal communication

What the job involves

• Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers
• Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency
• As a part of our team, you will bring deep expertise in quantitative modeling (statistical modeling, machine learning, experimentation, and causal inference) to build and refine models that inform how account teams operate
• You will apply generative AI within our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers
• You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems
• Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business
• This team defines and delivers a collection of advertising products that drive discovery and sales
• Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses
• We deliver billions of ads impressions, millions of clicks daily, and break fresh ground to create world-class products
• We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit with a broad mandate to experiment and innovate
• Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon!
• Turn customer needs into data science problems and actionable recommendations for your product, engineering, and sales partners
• This role combines analytical rigor, technical strength, product focus, and business understanding
• Build and apply LLM-based solutions (retrieval-augmented generation, prompting, and agentic workflows) to solve Ad Sales problems and generate seller-facing insights and recommendations
• Translate ambiguous business problems into data science problems, and build the statistical and machine learning models that complement LLM workflows, such as ranking, retrieval evaluation, segmentation, and forecasting
• Analyze large, complex datasets, including conversation and LLM interaction data, to surface insights, quantify gaps, and identify opportunities to improve our generative AI products
• Design and run experiments (A/B tests, offline and online evaluations, causal inference) and define metrics that measure the quality, accuracy, and business impact of LLM-driven solutions
• Write code (Python, SQL) to acquire, transform, and analyze data at scale, and partner with applied scientists and engineers to move solutions into production
• Present findings and recommendations clearly to technical and non-technical audiences, and mentor junior data scientists on your team