Capital One
Senior Manager, Data Science - Capital One Personal Loan
$209K–$286K
McLean, VA +3 · Manager · Full-time · Posted Oct 6, 2026
- Location
- McLean, VA
Richmond, VA
Chicago, IL
New York, NY - Experience
- Bachelor's: 7 years in data analytics; master's or quantitatively concentrated MBA: 5 years; PhD: 2 years. Also requires 2 years each in open-source programming for large-scale data analysis, machine learning, and relational databases.
- Education
- Bachelor's, master's, or PhD in a quantitative field; alternatively, an MBA with a quantitative concentration at the master's level.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Leads development and implementation of machine learning models for personal-loan acquisition, including customer selection, campaign optimization, underwriting, pricing, and verification.
What you'll do
- Build, train, evaluate, validate, and implement machine learning models.
- Partner with data scientists, engineers, and product managers to deliver customer-facing products.
- Translate analytical findings into business goals and develop talent across the team.
What they ask for
- Quantitative degree and data analytics experience: bachelor's plus 7 years, master's or quantitatively concentrated MBA plus 5 years, or PhD plus 2 years.
- At least 2 years using open-source programming languages for large-scale data analysis.
- At least 2 years working with machine learning.
- At least 2 years using relational databases.
Nice to have
- At least 1 year of AWS experience and at least 2 years managing people.
- At least 5 years using Python, Scala, or R for large-scale data analysis; at least 5 years working with machine learning.
Pay
USD $209,000 - $238,500 base salary (Chicago, IL); USD $229,900 - $262,400 base salary (McLean, VA); USD $250,800 - $286,200 base salary (New York, NY); USD $209,000 - $238,500 base salary (Richmond, VA)
Tools
Python, Conda, AWS, H2O, Spark, Scala, R
AI focus
Develops predictive and machine learning models for personal-loan acquisition, including list selection, campaign and channel optimization, underwriting, pricing, and verification.
Model-written summary · the original posting is authoritative