Paid Data Science Internship — 10 Weeks, Hybrid

Capital One; Richmond (VA); Hybrid; USD 121,000 - 147,000; Full time

Job summary

Capital One in Richmond, VA offers a paid Data Science Internship for ten weeks from June through August 2027. The internship requires you to be located in the continental United States with in-person attendance at your assigned location under Capital One's hybrid model.

Interns are evaluated for a full-time position and may start after graduation. The role focuses on data science, ML, and analytics, with opportunities to work on real business problems using open source tools.

Qualifications

• Currently pursuing one of the following with an expectation that the required degree will be obtained by August 2028 or earlier: a Master{S} Degree in a 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

Responsibilities

• 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

Skills

Python

R

SQL

Machine Learning

Data analysis

Education

Master's degree in quantitative field

MBA with quantitative concentration

Tools

Relational databases

Job description

Capital One in Richmond, VA offers a paid Data Science Internship for ten weeks from June through August 2027. The internship requires you to be located in the continental United States with in-person attendance at your assigned location under Capital One's hybrid model.

Interns are evaluated for a full-time position and may start after graduation. The role focuses on data science, ML, and analytics, with opportunities to work on real business problems using open source tools.