Capital One-posted 4 months ago
$130,000 - $156,000/Yr
Full-time • Intern
Hybrid • McLean, VA
Credit Intermediation and Related Activities

This is a full-time paid internship program spanning ten weeks from June through August 2026. Participation in the internship requires that you are located in the continental United States with in-person attendance at your assigned location, in accordance with Capital One's hybrid working model, for the duration of the program. Interns will be evaluated for a full-time position with their team and will work with their manager on identifying a start date upon graduation. This is a paid internship. This is a limited-time internship position, and Capital One will not sponsor a new applicant for employment authorization for this position. However, a full-time Data Science role, for which you may be considered upon completion of the internship (subject to business need, market conditions, and other factors) is eligible for employer immigration sponsorship.

  • Evaluate open-source and internally-developed modeling and analytics tools using real business data
  • Integrate internal data with external data sources and APIs to discover and implement actionable insights
  • Design and craft data science models to communicate solutions to customers and company leadership
  • Currently has, or is in the process of obtaining a Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration
  • Must be continuing in the same course of study of your Master's degree following completion of the internship
  • At least 6 months of experience or academic work using open source programming languages for data analysis
  • At least 6 months of experience or academic work using machine learning techniques
  • Direct experience with either Python, R or SQL
  • Experience or academic work in inferential statistics
  • Experience or academic work with relational databases
  • Experience or academic work with large scale data analysis
  • Comprehensive health benefits
  • Financial benefits
  • Inclusive set of benefits supporting total well-being
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