Principal Associate, Data Scientist - People Strategy & Analytics
Company: Capital One
Location: McLean, VA (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-06-03
About this role
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
People Strategy & Analytics brings data, analytics, and insights to shape critical talent decisions and strategy at Capital One. We work closely with HR partners and senior executives in shaping talent policy, automating real-time data, and improving talent decision-making. The team is comprised of people with diverse skills and backgrounds including: data analysts, data scientists, business analysts, HR specialists, project managers, and industrial/organizational psychologists.
As a Data Scientist on Capital One’s People Strategy & Analytics team, you’ll be on the leading edge of applying analytics to talent, combining artificial intelligence, machine learning, and social science to build models that seek to understand associate behavior, improve HR efficiency and tools, and inform strategies aimed at expanding Capital One’s talent advantage.
Role Description
In this role, you will:
- Build natural language processing and machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Apply expertise in using open source large language models (LLMs) through prompt engineering, retrieval-au...