Principal Associate, Quantitative Analysis

Capital One Capital One · Banking · McLean, VA

This role involves partnering with business lines to enhance modeling and analytical frameworks, creating novel analytical solutions, and identifying opportunities to apply quantitative methods and automation to improve business performance. The role requires applying expertise in econometric, statistical, and machine learning methods to generate insights and provide technical guidance, with a focus on building cloud-based solutions grounded in data.

What you'd actually do

  1. Partner with the various lines of business to enhance modeling and analytical framework.
  2. Work across Capital One entities to create novel analytical solutions to the challenging business problems.
  3. Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
  4. Collaborate in a cross-disciplinary team to build cloud based solutions grounded in data.
  5. Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.

Skills

Required

  • Master’s or foreign equivalent degree in Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Engineering, or a related quantitative field and 3 years of experience in quantitative analytics.
  • Statistical or econometric modeling
  • Linear and logistic regression
  • Programming in R, Python, or SQL
  • Presenting statistical concepts and research results to a non-statistical audience
  • Survival analysis modeling
  • Time-series analysis
  • Panel data analysis
  • Cross-sectional data analysis
  • Machine Learning
  • Analysis and management of large datasets

What the JD emphasized

  • quantitative analytics
  • Statistical or econometric modeling
  • Linear and logistic regression
  • Programming in R, Python, or SQL
  • Presenting statistical concepts and research results to a non-statistical audience
  • Survival analysis modeling
  • Time-series analysis
  • Panel data analysis (longitudinal data or cross-sectional time-series data)
  • Cross-sectional data analysis
  • Machine Learning
  • Analysis and management of large datasets (at least 1 million records)

Other signals

  • quantitative methods
  • automation solutions
  • machine learning
  • econometric
  • statistical
  • machine learning methods