Senior Quantitative Analyst - Model Risk & ML

Capital One National Association; McLean, Northern (VA, KY); Hybrid; USD 136,000 - 155,000; Full time

Job summary

Capital One in McLean, VA is seeking a Senior Associate, Quantitative Analyst to join the Model Risk Office. You will collaborate with model development and risk teams to enhance forecasting, validation, and documentation of quantitative models used across consumer lending.

The role requires strong background in statistics, econometrics, and programming (R, Python or SQL), plus the ability to communicate complex results to non-technical stakeholders.

Qualifications

• Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) or an MBA with a quantitative concentration.
• At least 1 year of experience in statistical or econometric modeling.
• Programming in R, Python or SQL.
• Presenting statistical concepts and research results to non-statistical audiences.
• Experience with survival, time-series, panel, or ML techniques is a plus.

Responsibilities

• Partner with the various lines of business to enhance modeling and analytical framework.
• Work across Capital One entities to create novel analytical solutions to challenging business problems.
• Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
• Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.
• Identify opportunities to apply quantitative methods or machine learning to improve business performance.

Skills

Quantitative analysis

Machine learning

Econometric analysis

Programming in R, Python or SQL

Communication of results

Documentation writing

Education

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

Job description

Capital One in McLean, VA is seeking a Senior Associate, Quantitative Analyst to join the Model Risk Office. You will collaborate with model development and risk teams to enhance forecasting, validation, and documentation of quantitative models used across consumer lending.

The role requires strong background in statistics, econometrics, and programming (R, Python or SQL), plus the ability to communicate complex results to non-technical stakeholders.