Capital One
Senior Manager, Data Scientist - US Card
$230K–$286K
McLean, VA +1 · Manager · Full-time · Posted Sep 25, 2026
- Location
- McLean, VA
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. Required degree may be in progress if obtained by the scheduled start date.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Develop and implement machine-learning solutions for US Card customer management, including behavioral prediction and valuation forecasting, in collaboration with cross-functional teams.
What you'll do
- Build machine-learning models through design, training, evaluation, validation, and implementation.
- Analyze large volumes of numeric and textual data to generate insights.
- Partner with data scientists, engineers, and product managers to deliver customer-facing products and translate technical work into business goals.
What they ask for
- Quantitative-field 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 1 year managing people.
- At least 5 years using Python, Scala, or R for large-scale data analysis, or at least 5 years with machine learning.
Pay
$229,900 - $262,400 USD base salary (McLean, VA); $250,800 - $286,200 USD base salary (New York, NY)
Tools
Python, Conda, AWS, H2O, Spark, Scala, R
AI focus
Develop machine-learning models for customer behavioral prediction and valuation forecasting, including model training, evaluation, validation, and implementation.
Model-written summary · the original posting is authoritative