Capital One
Principal Data Scientist - AI for Data and Assessment
$162K–$201K
McLean, VA +2 · Principal · Full-time · Posted Sep 23, 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 specified for a PhD. Preferred: at least 1 year with AWS and at least 3 years in Python, SQL, deep learning frameworks, and Natural Language Processing.
- Education
- Quantitative-field bachelor's degree, master's degree, or PhD; alternatively, an MBA with a quantitative concentration is listed with the master's-degree experience path.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Build and deploy machine learning solutions that support enterprise data lifecycle workflows and improve experiences for data and platform users.
What you'll do
- Collaborate with data scientists, software engineers, and product managers to deliver data products.
- Analyze large numeric and textual datasets using machine learning and related technologies.
- Develop models through design, training, evaluation, validation, and implementation, and communicate findings in business terms.
What they ask for
- A quantitative-field bachelor's degree plus 5 years of data analytics experience; or a quantitative-field master's degree or quantitatively concentrated MBA plus 3 years; or a quantitative-field PhD.
- Experience building, validating, and back-testing models, with knowledge of statistical methods and data analysis.
Nice to have
- At least 1 year of experience working with AWS.
- At least 3 years’ experience in Python, SQL, deep learning frameworks, or Natural Language Processing.
Pay
$161,800 - $184,600 USD base salary; $176,500 - $201,400 USD base salary
Tools
Python, Conda, AWS, H2O, Spark, SQL
AI focus
Build machine learning solutions for enterprise data lifecycle workflows, including emerging ML-powered experiences; model development includes training, evaluation, validation, and implementation.
Model-written summary · the original posting is authoritative