About the role#
This is a full-time, paid internship program spanning ten weeks from June through August 2027. As a Data Science intern, you will join a team focused on leveraging computing technologies to solve financial services challenges. You will contribute to the team from your first day by engaging in diverse experiences and building professional relationships across the company. This role is an opportunity to explore a long-term career path, as interns are evaluated for potential full-time positions upon completion of the program.
What you'll do#
- 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.
- Support machine learning, deep learning, or quantitative initiatives across the enterprise.
What you'll need#
- Currently pursuing a PhD in a quantitative field (such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Computer Science) with an expected graduation date of August 2029 or earlier.
- Must be continuing in the same course of study following 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.
- At least 6 months of experience with Python, R, or SQL.
- Experience in inferential statistics and large-scale data analysis is preferred.
Location & details#
- Locations: McLean, VA; Cambridge, MA; Chicago, IL; Richmond, VA; Plano, TX; San Francisco, CA; San Jose, CA; New York, NY.
- Work Modality: This is an on-site position. Interns must be located in the continental United States and attend their assigned location in person for the duration of the program.
- Sponsorship: Capital One will not sponsor a new applicant for employment authorization for this internship position.
