Capital One
Senior Manager, Data Scientist - Card Fraud Prevention
$230K–$286K
McLean, VA +1 · Manager · Full-time · Posted Aug 11, 2026
- Location
- McLean, VA
New York, NY - Experience
- Degree-dependent data analytics experience: 7 years with a bachelor's, 5 years with a master's or quantitatively focused MBA, or 2 years with a PhD; plus 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; alternatively, an MBA with a quantitative concentration. Degree must be 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
Leads data science work to detect and mitigate card fraud by developing and deploying machine learning models, and translating analytical results into customer-focused business outcomes.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver products.
- Develop machine learning models from design through training, evaluation, validation, and implementation.
- Analyze large volumes of numeric and textual data and communicate insights in business terms.
What they ask for
- Quantitative-field degree and data analytics experience: bachelor's plus 7 years, master's or quantitatively focused 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, 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, Ray, PyTorch, Kubernetes
AI focus
Build and deploy machine learning models for card-fraud detection and mitigation; the team also has an appetite for AI-based development.
Model-written summary · the original posting is authoritative