Capital One
Data Analytics Manager - PULSE Risk & Compliance
$150K–$205K
Riverwoods, IL +4 · Manager · Full-time · Posted Oct 9, 2026
- Location
- Riverwoods, IL
Richmond, VA
McLean, VA
Chicago, IL
New York, NY - Experience
- Bachelor’s route: at least 6 years in data analytics; Master’s route: at least 4 years in data analytics. Also requires at least 4 years of professional data analysis and 4 years of programming. Preferred: 7 years of professional data analysis; 4 years with Python, R, Spark or SQL; 1 year each in people management, project management, and Tableau.
- Education
- Bachelor’s Degree in a quantitative field, or Master’s Degree; 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
Build and apply analytics frameworks and models to investigate PULSE transaction anomalies and risk exposure while ensuring strategies are scalable, explainable, and compliant.
What you'll do
- Analyze large datasets and evaluate transaction risk, processes, and tests.
- Build, use, and validate models; improve data, processes, and reporting.
- Collaborate across business units and consult on production and data-storage system design.
What they ask for
- Bachelor’s Degree in a quantitative field plus at least 6 years of data analytics experience, or a Master’s Degree plus at least 4 years of data analytics experience; required degree must be obtained by the scheduled start date.
- At least 4 years of professional data analysis work.
- At least 4 years of programming experience.
Nice to have
- Master’s Degree in a Science, Technology, Engineering, Mathematics discipline.
- Experience with Python, R, Spark or SQL; people or project management; Tableau; or AWS.
Pay
$164,800 - $188,100 USD base salary; $149,800 - $171,000 USD base salary; $179,700 - $205,100 USD base salary; $149,800 - $171,000 USD base salary; $149,800 - $171,000 USD base salary
Tools
Python, R, Spark, SQL, Tableau, AWS
AI focus
Build and use models to test and validate data; apply machine learning and modeling in risk analysis with a focus on ethical, explainable, compliant strategies.
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