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Principal Quantitative Modeler

Principal Quantitative Modeler

CompanyCapital One
LocationMcLean, VA, USA
Salary$158600 – $181000
TypeFull-Time
Degrees
Experience LevelSenior, Expert or higher

Requirements

  • Strong understanding of quantitative analysis methods in relation to financial institutions.
  • Demonstrated track-record in machine learning and/or econometric analysis.
  • Experience utilizing model estimation tools.
  • Ability to clearly communicate modeling results to a wide range of audiences.
  • Drive to develop and maintain high quality and transparent model documentation.
  • Strong written and verbal communication skills.
  • Strong presentation skills.
  • Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.

Responsibilities

  • Partner with the various lines of business to enhance modeling and analytical framework.
  • Work across Capital One entities to create novel analytical solutions to the challenging business problems.
  • Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
  • Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.
  • Identify opportunities to apply quantitative methods or machine learning to improve business performance.
  • Apply deep expertise in econometric, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.
  • Providing technical guidance to business leadership.
  • Communicate technical subject matter clearly and concisely to individuals from various backgrounds.

Preferred Qualifications

  • PhD in Statistics, Economics, Mathematics, Financial Engineering, Operations Research, Engineering, Finance, Physics or related disciplines.
  • 1 year of experience with Python, R or other statistical analyst software.
  • 2 years of experience with data analysis.
  • 1 year of experience manipulating and analyzing large data sets.
  • Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, survival analysis, panel data models, design of experiments, decision trees, machine learning methods).