Sr Data Scientist, GenAI Economics and Analytics
Amazon • Seattle, Washington, United States
No Relocation
Posted: May 20, 2026
Additional Content
Description
- The Alexa For Shopping (formerly Rufus) Analytics team is seeking a customer-obsessed Sr Data Scientist to own and drive analytics strategy for GenAI-powered Shopping experiences. This role will partner
Description
- The Alexa For Shopping (formerly Rufus) Analytics team is seeking a customer-obsessed Sr Data Scientist to own and drive analytics strategy for GenAI-powered Shopping experiences. This role will partner closely with senior leaders to deliver high-quality insights that inform executive decision-making for the AI shopping assistant, Alexa for shopping. Successful candidate will demonstrate strong attention to detail, excellent written and verbal communication, and the ability to influence across organizations. In this role, you will mentor and set the bar for data science, economics, and engineering partners by establishing best practices for understanding customer behavior in AI-driven shopping experiences. You will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast, repeatable deep dives. This position will play a critical role in shaping product roadmap and investment decisions in a rapidly evolving GenAI space. The ideal candidate will operate effectively in ambiguous environments, exercise strong business judgment on high-impact, one-way door decisions, and continuously raise the bar for analytical rigor and operational excellence. You will work cross-functionally with product, engineering, and economics partners to deliver results for customers Key job responsibilities - Own the development of customer and shopping-mission cohorts to understand behavior with and without Alexa for shopping engagement across the end-to-end shopping journey. - Identify which query shapes and interaction patterns drive the most customer value for specific customer cohorts and shopping missions. - Build predictive models to estimate customer re-engagement and long-term adoption of Rufus based on interaction quality and downstream shopping outcomes. - Invent, operationalize, and publish scalable metrics and dashboards that surface actionable insights, enabling data-driven product growth and executive decision-making. - Partner closely with Product, Engineering, and Economics teams to translate analytical insights into roadmap priorities and customer-focused improvements. About the team The Alexa for shopping Analytics team focuses on understanding how GenAI-powered shopping tools are transforming customer behavior across the shopping lifecycle - from inspiration and problem-solving, to product research, selection, purchase, and post-purchase support. We build the foundational measurement frameworks that enable teams to evaluate performance, identify what AI experiences resonate most with customers, and uncover opportunities for improvement. Our work directly influences customer-centric product roadmap decisions and helps scale impactful, high-quality AI shopping experiences
Basic Qualifications
- - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 4+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression
Preferred Qualifications
- - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience - Experience managing data pipelines - Experience as a leader and mentor on a data science team Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.