Capital One
Senior Manager, Data Science - US Card (Upmarket Segments)
$209K–$286K
Richmond, VA +2 · Manager · Full-time · Posted Oct 27, 2026
- Location
- Richmond, VA
New York, NY
McLean, VA - Experience
- Data analytics: bachelor's + 7 years, master's or quantitative MBA + 5 years, or PhD + 2 years; also at least 2 years each in open-source programming for large-scale analysis, machine learning, and relational databases.
- Education
- Bachelor's, master's, or PhD in a quantitative field; alternatively, an MBA with a quantitative concentration for the master's pathway.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads data science work for US Card upmarket segments, developing and implementing machine learning models to uncover insights and support customer-focused products and business goals.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver customer-facing products.
- Develop machine learning models from design through training, evaluation, validation, and implementation.
- Translate analytical findings into business goals and lead talent development.
What they ask for
- Quantitative degree and data analytics experience: bachelor's plus 7 years, master's or quantitative 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 working with AWS and at least 1 year managing people.
- At least 5 years using Python, Scala, or R for large-scale data analysis; at least 5 years with machine learning.
Pay
$229,900 - $262,400 USD base salary; $250,800 - $286,200 USD base salary; $209,000 - $238,500 USD base salary
Tools
Python, Conda, AWS, H2O, Spark
AI focus
Build, validate, and implement machine learning models, including experience in clustering, classification, sentiment analysis, time series, and deep learning.
Model-written summary · the original posting is authoritative