Capital One
Principal Associate, Data Scientist - SBB Fraud
$162K–$185K
McLean, VA · Principal · Full-time · Posted Oct 28, 2026
- 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 with a PhD. Preferred: 3 years in machine learning; 1 year in deep learning/emerging AI; 3 years in Python, Dask, Spark, etc.; 3 years in SQL; 1 year with AWS.
- Education
- Bachelor's, master's, or PhD in a quantitative field; alternatively, an MBA with a quantitative concentration. The required 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
Build, deploy, and manage machine-learning models that detect and prevent fraud in Capital One’s Small Business Bank transactions and accounts.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver customer-facing products.
- Develop machine-learning models through design, training, evaluation, validation, and implementation.
- Analyze large volumes of numeric and textual data and translate findings into business goals.
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.
- Currently hold, or be obtaining by the scheduled start date, the qualifying degree.
Nice to have
- At least 3 years’ experience with machine learning; at least 1 year with deep learning or emerging AI; and at least 3 years with Python, Dask, Spark, or similar.
- At least 3 years’ experience with SQL and at least 1 year working with AWS.
Pay
$161,800 - $184,600 USD annual base salary
Tools
Python, Conda, AWS, H2O, Spark, Dask, SQL
AI focus
Develop and manage fraud-detection machine-learning models; preferred experience includes deep learning and emerging AI such as graphs, embeddings, sequence models, and transformer models.
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