Capital One
Principal Associate, Data Scientist - Recommendation & Personalization Systems
$162K–$201K
McLean, VA +2 · Principal · Full-time · Posted Sep 18, 2026
- Location
- McLean, VA
New York, NY
San Jose, CA - Experience
- 5 years of data analytics with a bachelor’s degree; 3 years with a master’s degree or quantitatively concentrated MBA; no years stated for a PhD. Preferred: 3 years in Python, Scala, or R, machine learning, and SQL; 1 year with AWS.
- 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
Develop and deploy large-scale personalized recommendation and machine learning systems for Capital One’s web and mobile customer experiences.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver customer-focused products.
- Analyze large volumes of numeric and textual data using data science technologies.
- Build machine learning models through design, training, evaluation, validation, and implementation.
What they ask for
- Quantitative-field bachelor’s degree plus 5 years of data analytics experience; or quantitative-field master’s degree or quantitatively concentrated MBA plus 3 years; or quantitative-field PhD.
- Degree must be held or expected by the scheduled start date.
Nice to have
- At least 3 years of experience in Python, Scala, or R; machine learning; and SQL.
- At least 1 year of experience working with AWS.
Pay
$161,800 - $184,600 USD base salary; $176,500 - $201,400 USD base salary; $176,500 - $201,400 USD base salary
Tools
Python, Conda, AWS, H2O, Spark, Scala, R, SQL
AI focus
Research and develop personalized recommendation systems, including homegrown Foundation Models, Reinforcement Learning, Causal Inference, and Transformer-based architectures.
Model-written summary · the original posting is authoritative