Senior Quantitative Analyst, Model Risk & Capital Markets

Capital One; McLean (VA); On-site; USD 162,000 - 185,000; Full time

Job summary

Capital One is seeking a Principal Quantitative Analyst to join the Model Risk Office in McLean, VA. You will lead validation of balance sheet forecasting and economic stress test models, collaborating with teams to ensure accuracy and regulatory readiness.

You will apply deep mathematics and ML methods, guide leadership, and communicate complex results clearly. This role emphasizes end-to-end ownership, robust documentation, and cross-functional impact.

Qualifications

• Master’s degree in statistics, economics, OR a related quantitative field (or MBA with quantitative focus) by start date.
• PhD in a quantitative field is acceptable.
• At least 3 years of experience in quantitative analytics.
• Experience with risk modeling, financial time series, or capital markets.

Responsibilities

• Develop and enhance Capital Markets modeling and analytical framework such as deposit predictions, derivatives models, and fixed income models.
• Collaborate across entities to create novel analytical solutions to business problems.
• Identify opportunities to apply quantitative methods and automation to improve performance and efficiency.
• Build cloud-based solutions grounded in data with cross-disciplinary teams.
• Own the model validation process end-to-end from conception to monitoring, and communicate findings.

Skills

Quantitative analysis

Python

C++

Statistical modeling

Communication

Education

Master's degree in statistics, economics, operations research, analytics, mathematics, computer science, or related field

PhD in a quantitative field

Tools

Python

C++

R

SQL

Job description

Capital One is seeking a Principal Quantitative Analyst to join the Model Risk Office in McLean, VA. You will lead validation of balance sheet forecasting and economic stress test models, collaborating with teams to ensure accuracy and regulatory readiness.

You will apply deep mathematics and ML methods, guide leadership, and communicate complex results clearly. This role emphasizes end-to-end ownership, robust documentation, and cross-functional impact.