Senior Data Science Manager: Model Risk & Impact Leader

ITSMF; Chicago (IL); On-site; USD 209,000 - 262,000; Full time

Job summary

Capital One is seeking a Senior Manager, Data Science - Model Risk Office to lead data science initiatives across underwriting models and risk governance. You will guide cross-functional teams, develop scalable ML solutions on a modern tech stack, and ensure models meet business and regulatory standards while driving decision quality.

The role emphasizes leadership, advanced analytics, cloud and open-source tooling, and collaboration with product, engineering, and risk teams to maximize business

Qualifications

• Bachelor’s degree with 7+ years analytics experience or Master’s with 5+ years or PhD with 2+ years in quantitative analytics.
• 2+ years using open source languages for large-scale data analysis.
• 2+ years of machine learning experience.
• 2+ years of working with relational databases.

Responsibilities

• Partner with cross-functional data scientists, engineers and product managers to deliver data products.
• Leverage Python, Conda, AWS, H2O, Spark and related tools to extract insights from large datapools.
• Build ML models through design, training, evaluation, validation and implementation.
• Translate complex work into tangible business goals.

Skills

Cross-functional collaboration

Open-source languages

Machine Learning

Data analytics

Relational databases

Cloud computing

Education

Bachelor's Degree in a quantitative field

Master’s Degree in a quantitative field or MBA with quantitative concentration

PhD in a quantitative field

Tools

Python

Conda

AWS

H2O

Spark

Job description

Capital One is seeking a Senior Manager, Data Science - Model Risk Office to lead data science initiatives across underwriting models and risk governance. You will guide cross-functional teams, develop scalable ML solutions on a modern tech stack, and ensure models meet business and regulatory standards while driving decision quality.

The role emphasizes leadership, advanced analytics, cloud and open-source tooling, and collaboration with product, engineering, and risk teams to maximize business