Capital One
Senior Manager, Data Science - Model Risk Office
$209K–$262K
McLean, VA +2 · Manager · Full-time · Posted May 6, 2026
- Location
- McLean, VA
Richmond, VA
Chicago, IL - Experience
- 2–7 years of data analytics experience, depending on degree; 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 may be in progress, with expected completion 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
Identify, quantify, and validate model risks across business domains, build challenger machine learning models, and contribute to model governance, including risks related to Generative AI.
What you'll do
- Partner with data scientists, software engineers, and product managers to identify and quantify model risks.
- Build machine learning models to challenge production models and validate models across business domains; present risks and business impacts to executives.
- Contribute to the model governance framework for future models.
What they ask for
- Quantitative degree and data analytics experience through one of these routes: 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 utilizing relational databases.
Nice to have
- At least 1 year working with AWS or managing people; at least 5 years with Python, Scala, or R for large scale data analysis or machine learning.
- PhD in a STEM field plus 4 years of data analytics experience.
Pay
Chicago, IL: $209,000 - $238,500 USD base salary; McLean, VA: $229,900 - $262,400 USD base salary; Richmond, VA: $209,000 - $238,500 USD base salary
Tools
PyTorch, Hugging Face, LangChain, Vector Databases, LLMOps, Python, Scala, R
AI focus
Model risk work involving Generative AI; use of frameworks and orchestration tools to analyze multimodal data and validate models.
Model-written summary · the original posting is authoritative