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Senior Product Manager, AI Enablement - Analytics: Capital One Shopping (Remote-Eligible)

Capital One · Remoto Brasil · Flexible / Remote

Publicada em 29/10/2026

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Senior Product Manager, AI Enablement - Analytics: Capital One Shopping (Remote-Eligible)Come join our growing team in Capital One Shopping - the AI Enablement team builds and owns the AI products and platforms the rest of the organization runs on. Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry.We're looking for a Senior Product Manager with deep data platform experience to own Shopping's agentic analytics platform. Applied AI experience is a plus, and we value candidates who are builders and actively use AI tools (e.g., Claude Code, Codex, Cursor) to prototype rather than specify, and who'd rather ship a PoC than write a doc about it. Show us what you've built.Capital One Product FrameworkIn this role, you'll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management:Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutionsBusiness Focused - Delivers game-changing outcomes by focusing on leverage and execution excellenceTechnology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term valueIntegrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignmentWhat we are looking for:Deep experience with enterprise data and how it's defined and governed (semantic and metrics layers, data catalogs, ontologi
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