Data Science Intern

Capital One Financial

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
McLean, VACambridge, MAChicago, ILRichmond, VAPlano, TXSan Francisco, CASan Jose, CANew York, NY
Employment
Full-time
Posted
99 days ago
Freshness
Confirmed live today

Market check

Salary context

How this pay compares to similar roles

Similar $164k
$102k $227k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $114,400–$214,500.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Data Science Intern

Current PhD - Data Science Internship - Summer 2027 involves joining a high-performing team to solve financial services challenges using groundbreaking techniques. Interns will support machine learning, deep learning, or quant initiatives across the enterprise. Day-to-day responsibilities include evaluating open-source and internally-developed modeling and analytics tools using real business data, integrating internal data with external sources and APIs to discover actionable insights, and designing data science models to communicate solutions to leadership. Candidates must possess experience in open-source programming languages for data analysis, machine learning techniques, and proficiency in Python, R, or SQL. Preferred skills include inferential statistics, relational databases, and large scale data analysis. The role focuses on mining data for insights into behaviors, intent, and sentiment to improve financial lives.

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 actionable insights.
  • Design and craft data science models to communicate solutions to customers and leadership.
  • Develop and implement machine learning, deep learning, or quantitative initiatives across the enterprise.
  • Mine unstructured data sources to identify patterns in behaviors, intent, and sentiment.
  • Experiment with new combinations of tools, techniques, and feature engineering approaches.
  • Share technical ideas with teammates and business partners through verbal and written channels.

What we're looking for

  • Must be currently pursuing a PhD in a quantitative field with an expected completion date by August 2029.
  • Must continue in the same PhD course of study following the completion of the internship.
  • Must have at least 6 months of experience or academic work using open source programming languages for data analysis.
  • Must have at least 6 months of experience or academic work using machine learning techniques.
  • Must have at least 6 months of experience with either Python, R, or SQL.
  • Must be located in the continental United States for in-person attendance.
  • Experience or academic work in inferential statistics (preferred).
  • Experience or academic work with relational databases (preferred).
  • Experience or academic work with large scale data analysis (preferred).

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