Manager, Card Intelligence & ML Product Strategy

Capital One Group; Chicago, Northern (IL, KY); Hybrid; USD 150,000 - 171,000; Full time

Job summary

Capital One is seeking a Manager, Product Management for Card Intelligence in Chicago to guide ML-enabled product initiatives and shape the roadmap. You will define problem statements, align cross-functional partners, and own a three-year ML infrastructure plan linked to business outcomes.

You’ll collaborate with data scientists and engineers to drive agile delivery, balance risk with innovation, and deliver scalable, reusable capabilities that enhance customer experiences.

Qualifications

• Bachelor's or Master’s Degree in a quantitative field or Business/Marketing OR Bachelor's degree in any field and at least 3 years of Product Management experience
• Experience translating business strategy into consumer facing digital products
• Prior experience with data engineering problems and platforms, machine learning infrastructure, MLOps, software engineering

Responsibilities

• Define clear and actionable problem statements guiding iterative software delivery
• Leverage customer insights to shape priorities and roadmaps while aligning stakeholders
• Own three-year ML infrastructure and model delivery roadmaps tied to business outcomes
• Identify leverage points in complex systems and define success metrics with data
• Lead agile ceremonies and partner with technology teams on design decisions
• Deliver reusable, extensible capabilities and monitor key metrics for improvement

Skills

Product management

Data-driven decision making

Stakeholder alignment

Agile delivery

Education

Bachelor’s or Master’s Degree in a quantitative field or Business/Marketing

Tools

ML infrastructure

MLOps

Data engineering platforms

Software engineering

Job description

Capital One is seeking a Manager, Product Management for Card Intelligence in Chicago to guide ML-enabled product initiatives and shape the roadmap. You will define problem statements, align cross-functional partners, and own a three-year ML infrastructure plan linked to business outcomes.

You’ll collaborate with data scientists and engineers to drive agile delivery, balance risk with innovation, and deliver scalable, reusable capabilities that enhance customer experiences.