Senior Quantitative Modeler - Credit Risk & Forecasting

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

Job summary

Capital One is seeking a Principal Quantitative Modeler to lead econometric and machine learning modeling across credit risk and capital needs. You will collaborate with multiple business units to develop scalable cloud-based models and analytics, ensuring robust documentation and clear communication of results.

The role requires advanced degrees in quantitative fields and several years of modeling experience, with a strong emphasis on statistical methods, ML, and large dataset handling.

Qualifications

• Master’s degree in a quantitative field or MBA with a quantitative concentration plus 3 years of experience in quantitative analytics
• PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science)
• At least 3 years of experience in statistical or econometric modeling
• At least 3 years of experience in regression and machine learning methods
• Ability to clearly communicate modeling results to a wide audience
• Experience with model estimation tools and large datasets (>1M records)

Responsibilities

• Partner with business lines to enhance modeling and analytical framework
• Create novel analytical solutions across Capital One entities
• Apply quantitative methods and automation to improve performance
• Collaborate in a cross-disciplinary team for cloud-based solutions
• Own the model development process from conceptualization to monitoring

Skills

Quantitative analysis

Statistical methods

Machine learning

Econometrics

Python

R

SQL

Model validation

Communication

Data exploration

Education

Master’s degree in quantitative field

PhD in quantitative field

Tools

SQL

Job description

Capital One is seeking a Principal Quantitative Modeler to lead econometric and machine learning modeling across credit risk and capital needs. You will collaborate with multiple business units to develop scalable cloud-based models and analytics, ensuring robust documentation and clear communication of results.

The role requires advanced degrees in quantitative fields and several years of modeling experience, with a strong emphasis on statistical methods, ML, and large dataset handling.