Senior Quantitative Risk Manager — Model Risk

capitalone; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Job summary

Capital One is seeking a Senior Manager for Quantitative Analysis to lead advanced modeling efforts and partner with model development and model risk teams. The role focuses on Loan Loss Forecasting and ACL framework, using Python or R, ML, and econometric methods across large datasets.

The ideal candidate has 5+ years in quantitative analytics, strong communication, and experience with Agile development. Sponsorship available; competitive salary and incentives provided.

Qualifications

• Master’s degree in a quantitative field (Statistics, Economics, OR, Analytics, Mathematics, CS) or MBA with quantitative concentration plus 5 years analytics experience
• PhD in a quantitative field plus 2 years analytics experience
• 5+ years in statistical/econometric modeling and in linear/logistic regression
• 5+ years programming in R, Python, or SQL; presenting results to non-technical audiences
• 5+ years in at least 3 of: survival analysis, time-series, panel data, cross-sectional data, ML, large datasets

Responsibilities

• Stay at the cutting edge of analytics and tools.
• Develop alternative model approaches to assess design and risk.
• Understand business portfolios and model use contexts.
• Apply econometric, statistical and ML methods to model risks and opportunities.
• Present complex results to management and stakeholders clearly.
• Maintain high-quality documentation and transparent processes.
• Leverage open-source tools to extend the framework.

Skills

Statistical modeling

Regression analysis

Programming in Python/R/SQL

Communicating results

Agile development

Education

Master’s degree in quantitative field

PhD in quantitative field

Job description

Capital One is seeking a Senior Manager for Quantitative Analysis to lead advanced modeling efforts and partner with model development and model risk teams. The role focuses on Loan Loss Forecasting and ACL framework, using Python or R, ML, and econometric methods across large datasets.

The ideal candidate has 5+ years in quantitative analytics, strong communication, and experience with Agile development. Sponsorship available; competitive salary and incentives provided.