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

Capital One•McLean, VA

1d•$182,500 - $249,900•Remote

About The Position

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. In 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 solutions, Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence, Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value, Integrated 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 alignment.

Requirements

At least 4 years of experience in Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's or Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field), Business or Marketing OR Bachelor's degree in any field and at least 4 years of Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience
Deep experience with enterprise data and how it’s defined and governed (semantic and metrics layers, data catalogs, ontologies, warehouse and BI, etc.)
Familiarity with tools across the modern data stack (dbt, LookML, Snowflake, Databricks, Palantir Foundry, Looker, Mode, etc.)
Familiarity with how AI agents work across structured data (text-to-SQL, tool use, evals, and where these systems fail)
Someone who has adjudicated metric disputes and made the decision stick
A builder who would rather be in the tools prototyping than be dependent on someone else to run them
Comfort with backend and internal platform products, where the users are diverse business and technical teams, and the measure is whether they trust the outputs
A strategic thought leader who can create a compelling vision and story to present to senior executives and inspire direct and partner teams
A strong communicator who can advance initiatives and create consensus through clear, concise, and contextually relevant messaging
Someone who works with minimal direction and a mandate that’s still taking shape
Deep work experience handling large data files using SQL, Python, and/or R

Nice To Haves

Applied AI experience is a plus
7+ years of Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience, including ownership of an internal platform or a production deployment into a real operating environment
4+ years of experience working directly in data, with a deep proficiency in SQL
Experience defining and governing metrics across teams that did not agree
Experience with semantic layers, metrics layers, or ontologies (dbt, LookML, Cube, Palantir Foundry, or comparable)

Responsibilities

Partner with platform engineers to build and operate AI products that teams across Shopping depend on, starting with an agentic analytics platform
Understand the enterprise data requirements and ensure the system’s compliance with enterprise patterns
Define what a system needs to know to be trusted (the data, the definitions, the context behind both)
Set the boundaries for what agents can and can’t do, and prove those boundaries hold in practice
Relentlessly push to understand user and stakeholder needs and ensure they are considered in prioritization and trade-off discussions
Make each successive deployment cheaper and faster than the last
Build and maintain strong relationships with leaders and stakeholders that depend on the capabilities and performance of our platforms
Define, socialize, and monitor key performance indicators to understand the evolution and success of the project