Director, Quantitative Analysis - Model Risk Office

Capital One

Richmond, VA, US
Richmond, va: $244,700 - $279,200; mclean, va: $26...
Quantitative analysis methods
Model development and validation
Econometric, statistical, and machine learning methods
As a Director, Quantitative Analysis within the Model Risk Office, you will be part of the model validation team, leading the validation and model risk strategies for Allowance (CECL) and CCAR stress testing models

Job Summary

  • As a Director, Quantitative Analysis within the Model Risk Office, you will be part of the model validation team, leading the validation and model risk strategies for Allowance (CECL) and CCAR stress testing models.
  • You will enhance your technical and analytical skills, while also working closely with business leaders to influence business and modeling strategies.
  • With a network of over 500 quantitative analysts and data scientists, we’ve created a dynamic environment with plenty of room for you to learn, grow, and realize your full potential.

Matching Summary

As a Director, Quantitative Analysis within the Model Risk Office, you will be part of the model validation team, leading the validation and model risk strategies for Allowance (CECL) and CCAR stress testing models.

Salary

Richmond, VA: $244,700 - $279,200; McLean, VA: $269,100 - $307,200; Bonus/Equity: Performance based incentive compensation; Benefits: Comprehensive, competitive, and inclusive set of health, financial and other benefits

Skills & Requirements

Must-have

  • Quantitative analysis methods
  • Model development and validation
  • Econometric, statistical, and machine learning methods
  • Statistical or econometric modeling
  • Linear and logistic regression
  • Programming in R, Python, or SQL

Nice-to-have

  • Cloud computing and machine learning technologies
  • Data-driven decision-making
  • Culture of mutual respect, excellence, and innovation
  • Processes, controls, and good governance

Key Requirements

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

Work Rights

Not specified

Sponsorship: available

Tailored Resume

Cover Letter