Senior Manager, Quantitative Analysis - Model Risk Office

Responsibilities

• Partner with model development teams to advance Loan Loss Forecasting and Allowance for Credit Losses (ACL) frameworks.
• Develop alternative model approaches to assess design and advance future capabilities using machine learning and cloud computing.
• Identify and assess technical issues in econometric, statistical, and machine learning modeling to mitigate model risks.
• Communicate complex technical subject matter and research results clearly to non-specialist audiences and senior management.
• Maintain model efficiency and accuracy through continuous improvement and high-quality, transparent documentation.
• Leverage open-source technologies to identify opportunities within existing frameworks.

Requirements

• Master's degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, etc.) plus 5 years of experience, or a PhD in a quantitative field plus 2 years of experience.
• At least 5 years of experience in statistical or econometric modeling.
• Proficiency in programming with Python, R, or SQL.
• Experience with machine learning and managing large datasets.
• Strong ability to present statistical concepts and research results to non-statistical audiences.
• Experience working with Agile development methodologies.

Preferred Qualifications

• 6+ years of experience with Python, R, or other statistical analysis software.
• 6+ years of experience in statistical modeling, regression analytics, or machine learning.
• 2+ years of experience in people management.

Benefits

• Comprehensive and inclusive health, financial, and well-being benefits.
• Performance-based incentive compensation, including potential cash bonuses or long-term incentives.
• Opportunities for professional growth and career advancement within a leading data-driven company.

About the Company

Capital One is a leader in data-driven decision-making, using cutting-edge technology and statistical modeling to personalize financial services. We operate at a massive scale, leveraging cloud computing and machine learning to help customers manage their financial lives more effectively.