Capital One
Senior Director, Data Scientist - US Card
$315K–$392K
McLean, VA +2 · Director · Full-time · Posted Oct 26, 2026
- Location
- McLean, VA
New York, NY
Cambridge, MA - Experience
- Data analytics: 11 years with a quantitative bachelor’s degree, 9 years with a quantitative master’s degree or quantitatively concentrated MBA, or 6 years with a quantitative PhD. Also 6 years each in open-source programming for large-scale data analysis, machine learning, and relational databases.
- Education
- Quantitative bachelor’s, master’s, or PhD as specified; a quantitative MBA concentration is an alternative to the master’s degree.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads data science and machine-learning work across the US credit-card lifecycle, turning customer data insights into models and products that support business strategy and customer experiences.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver customer-facing products.
- Develop machine-learning models from design and training through evaluation, validation, and implementation.
- Translate analytical insights into business goals and help guide data-driven decisions.
What they ask for
- Bachelor’s degree in a quantitative field plus 11 years of data analytics experience; or a quantitative master’s degree or quantitatively concentrated MBA plus 9 years; or a quantitative PhD plus 6 years.
- At least 6 years using open-source programming languages for large-scale data analysis.
- At least 6 years working with machine learning.
- At least 6 years using relational databases.
Nice to have
- At least 1 year working with AWS.
- At least 4 years managing people.
Pay
$314,800 - $359,300 USD base salary (Cambridge, MA); $314,800 - $359,300 USD base salary (McLean, VA); $343,400 - $392,000 USD base salary (New York, NY)
Tools
Python, Conda, AWS, H2O, Spark
AI focus
Build and deploy machine-learning models across the credit-card lifecycle, including marketing, acquisitions, underwriting, and fraud prevention.
Model-written summary · the original posting is authoritative