Senior Product Manager, ML Platforms & Card Intelligence

Capital One; McLean (VA); On-site; USD 165,000 - 188,000; Full time

Job summary

Capital One is seeking a Manager, Product Management for Card Intelligence Acquisitions Models to define capabilities for ML platforms and collaborate with data scientists, engineers, and business partners. You will partner with leaders across business, data science, and engineering to bring models to market and drive scalable, customer-centric ML products.

The role focuses on delivering machine learning platform and tool requirements, shaping architecture patterns, and leading a product pod

Qualifications

• 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 related) or Business/Marketing; 3 years PM experience if Bachelor's only.
• 3+ years of Product Management experience.

Responsibilities

• Balance business and technology product requirements to drive consensus across partners.
• Drive delivery of deploying production ML models.
• Use systems thinking to design and deliver ML platforms, tools and standards on a cross-functional team.
• Look end-to-end to help drive integration, adoption and scaling of models.
• Help manage prioritization and investment with cross-functional teams to balance retraining, refitting, and rebuilding models while operating current models.
• Define and operate a product pod across DS and Tech to drive standard agile management practices, while communicating with senior management stakeholders.

Skills

Product Management

Education

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

Job description

Capital One is seeking a Manager, Product Management for Card Intelligence Acquisitions Models to define capabilities for ML platforms and collaborate with data scientists, engineers, and business partners. You will partner with leaders across business, data science, and engineering to bring models to market and drive scalable, customer-centric ML products.

The role focuses on delivering machine learning platform and tool requirements, shaping architecture patterns, and leading a product pod