Capital One
Senior Manager, Data Science - US Card (Resiliency Intelligence)
$230K–$286K
McLean, VA +2 · Manager · Full-time · Posted Sep 29, 2026
- Location
- McLean, VA
New York, NY
Cambridge, MA - Experience
- Bachelor's: 7 years; master's or quantitatively concentrated MBA: 5 years; PhD: 2 years, all in data analytics. Also at least 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, or an MBA with a quantitative concentration (with the corresponding experience listed).
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads data science work to develop and implement models that predict customer needs and recommend personalized financial-resiliency solutions at scale.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver customer-focused products.
- Build machine learning models through design, training, evaluation, validation, and implementation.
- Analyze large volumes of numeric and textual data and translate findings into business goals.
What they ask for
- Quantitative degree and 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
- PhD in a STEM field plus 4 years of data analytics experience; at least 1 year managing people.
- At least 1 year working with AWS; or 5 years using Python, Scala, or R for large-scale data analysis or working with machine learning.
Pay
USD $229,900 - $262,400 base salary (Cambridge, MA); USD $229,900 - $262,400 base salary (McLean, VA); USD $250,800 - $286,200 base salary (New York, NY)
Tools
Python, Conda, AWS, H2O, Spark, XGBoost, scikit-learn, stats models
AI focus
Uses supervised and reinforcement learning to predict customer needs and recommend personalized solutions; develops and deploys machine learning models.
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