Senior Manager, Quantitative Analysis - Model Risk Office

Capital One Capital One · Banking · McLean, VA

Senior Manager role focused on quantitative analysis within the Model Risk Office at Capital One. The role involves partnering with model development and risk teams to advance the Loan Loss Forecasting and ACL framework, assessing model design, and ensuring model quality and transparency. Requires strong experience in statistical and machine learning modeling, Python/R, and communicating technical concepts to various stakeholders, including regulators.

What you'd actually do

  1. Partner with high-performing model development teams and model risk teams responsible for advance Capital One’s Loan Loss Forecasting and Allowance for Credit Losses (ACL) framework.
  2. Understand technical issues in econometric, statistical, and machine learning modeling and apply these skills toward developing models and assessing model risks and opportunities.
  3. Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management.
  4. Maintain the efficiency and accuracy of our models through continuous improvement and application of best practices.
  5. Develop and maintain high quality and transparent documentation.

Skills

Required

  • Master's degree in a quantitative field or MBA with quantitative concentration plus 5 years of experience, OR PhD in a quantitative field plus 2 years of experience
  • 5 years of experience in statistical or econometric modeling
  • 5 years of experience in linear and logistic regression
  • 5 years of experience in programming in R, Python, or SQL
  • 5 years of experience presenting statistical concepts and research results to non-statistical audience
  • 5 years of experience in at least 3 of the following: Survival analysis modeling, Time-series analysis, Panel data analysis, Cross-sectional data analysis, Machine learning, Analysis and management of large datasets (>1M records)

Nice to have

  • 6 years of experience with Python, R or other statistical analyst software
  • 6 years of experience in statistical modeling or regression analytics or machine learning
  • 2 years of experience managing people
  • Experience working with Agile development methodologies
  • Strong grasp of econometric theory and methodologies
  • Desire to remain on the leading edge of analytical technology with a passion for the newest and most innovative tools.

What the JD emphasized

  • model risk
  • quantitative analysis
  • machine learning
  • regulatory

Other signals

  • model risk management
  • quantitative analysis
  • machine learning
  • regulatory compliance