Sr. BIE, GenAI Economics and Analytics
Summary
Owns analytics for GenAI-powered shopping tools, building metrics and dashboards to measure customer adoption and guide product decisions for Alexa for Shopping.
The Alexa for Shopping (formerly Rufus) Analytics team is seeking a customer-obsessed Sr BIE to own and drive analytics strategy for our GenAI-powered Shopping experiences. You will partner closely with senior leaders to deliver high-quality insights that inform executive decision-making for the AI shopping assistant, Alexa for Shopping. The successful candidate brings strong attention to detail, excellent written and verbal communication, and the ability to influence across organizations.
In this role you will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast repeatable deep dives. A BIE typically wears many hats, but this role weights the science side of the craft more heavily. You will help shape the product roadmap and investment decisions in a fast-moving GenAI space.
The ideal candidate operates effectively in ambiguity, exercises strong business judgment on high-impact one-way-door decisions, and continuously raises the bar for analytical rigor and operational excellence. You will work cross-functionally with product, science, engineering and economics partners to deliver results for customers.
Key job responsibilities
Build and maintain the reporting layer and knowledge graph that power our in-house conversational analytics agent.
Partner with product teams to define and maintain the KPIs behind go/no-go product decisions.
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 and Engineering to raise the bar on how we log and model customer engagement data.
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
In this role you will invent and scale metrics that measure customer adoption and habituation, and build agentic, automated analytical workflows that enable fast repeatable deep dives. A BIE typically wears many hats, but this role weights the science side of the craft more heavily. You will help shape the product roadmap and investment decisions in a fast-moving GenAI space.
The ideal candidate operates effectively in ambiguity, exercises strong business judgment on high-impact one-way-door decisions, and continuously raises the bar for analytical rigor and operational excellence. You will work cross-functionally with product, science, engineering and economics partners to deliver results for customers.
Key job responsibilities
Build and maintain the reporting layer and knowledge graph that power our in-house conversational analytics agent.
Partner with product teams to define and maintain the KPIs behind go/no-go product decisions.
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 and Engineering to raise the bar on how we log and model customer engagement data.
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
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