Capital One
Director, Data Science
$245K–$335K
McLean, VA +4 · Director · Full-time · Posted Sep 28, 2026
- Location
- McLean, VA
San Francisco, CA
Cambridge, MA
Richmond, VA
New York, NY - Experience
- Degree-dependent data analytics experience: 9 years with a bachelor's, 7 years with a master's or quantitative MBA, or 4 years with a PhD; also 4+ years each in open-source large-scale data analysis, production AI/ML, and A/B testing.
- Education
- Bachelor's, master's, or PhD in a quantitative field; alternatively, an MBA with a quantitative concentration at the master's-degree experience level.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Design and build agentic AI/ML products and lead experiments and impact analysis to guide enterprise strategy and business value.
What you'll do
- Partner with data scientists, AI/ML engineers, and product managers to deliver enterprise products.
- Develop machine-learning models from design through implementation and analyze large numeric and textual datasets.
- Design A/B tests, model telemetry, and translate results into AI strategy and guidance for senior leadership.
What they ask for
- Quantitative-field bachelor's degree plus 9 years, master's degree or quantitatively concentrated MBA plus 7 years, or PhD plus 4 years of data analytics experience.
- At least 4 years using open-source programming languages for large-scale data analysis.
- At least 4 years building and deploying AI/ML models in production.
- At least 4 years designing and analyzing A/B tests.
Nice to have
- 3+ years working with AWS; 5+ years using Python, Scala, or R for large-scale data analysis.
- 5+ years of machine learning and 5+ years of Spark experience.
Pay
USD $269,100 - $307,200 base salary (Cambridge, MA); USD $269,100 - $307,200 base salary (McLean, VA); USD $293,600 - $335,100 base salary (New York, NY); USD $244,700 - $279,200 base salary (Richmond, VA); USD $293,600 - $335,100 base salary (San Francisco, CA)
Tools
Python, Conda, AWS, H2O, Spark, Scala, R
AI focus
Build agentic AI products, including autonomous coding agents, context engineering, and agentic model-development lifecycle; develop and evaluate AI/ML models and measure product impact.
Model-written summary · the original posting is authoritative