Capital One
Manager, Data Science - US Card - Marketing
$197K–$246K
McLean, VA +2 · Manager · Full-time · Posted Oct 19, 2026
- Location
- McLean, VA
New York, NY
Cambridge, MA - Experience
- 1–6+ years performing data analytics, depending on degree; at least 1 year 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; a quantitative-concentration MBA is an alternative to a master's. Degree must be obtained by the scheduled start date.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Leads the development and deployment of machine-learning solutions that personalize marketing and optimize customer acquisition across customer touchpoints.
What you'll do
- Build models through design, training, evaluation, validation, and implementation.
- Partner with data scientists, engineers, product managers, and business stakeholders to deliver customer-focused products and measurable business value.
- Translate complex analytical work into business goals and strategic decisions.
What they ask for
- Quantitative degree and data analytics experience: bachelor's plus 6 years, master's or quantitative MBA plus 4 years, or PhD plus 1 year.
- At least 1 year using open-source programming languages for large-scale data analysis.
- At least 1 year working with machine learning.
- At least 1 year using relational databases.
Nice to have
- At least 1 year working with AWS.
- At least 4 years using Python, Scala, or R for large-scale data analysis; machine learning; or SQL.
Pay
$197,300 - $225,100 USD base salary (Cambridge, MA); $197,300 - $225,100 USD base salary (McLean, VA); $215,200 - $245,600 USD base salary (New York, NY)
Tools
Python, Conda, AWS, H2O, Spark, XGBoost, scikit-learn, statsmodels
AI focus
Uses supervised and reinforcement learning to predict customer needs, recommend offers, and optimize customer acquisition and marketing engagement.
Model-written summary · the original posting is authoritative