Capital One
Senior Associate, Data Scientist - Consumer Credit Risk Models and Data
$136K–$155K
McLean, VA · Senior · Full-time · Posted Aug 3, 2026
- Experience
- 2 years of data analytics experience with a quantitative bachelor’s degree; alternatively, a quantitative master’s degree or quantitatively concentrated MBA. Preferred: 2+ years in Python, Scala, or R, machine learning, and SQL.
- Education
- Bachelor’s degree in a quantitative field plus 2 years of data analytics experience, or a master’s degree in a quantitative field or an MBA with a quantitative concentration.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Deploys and modernizes model pipelines and platforms for consumer credit risk models that support loss forecasting, stress testing, capital allocation, and strategic decisions.
What you'll do
- Partner with data scientists, software engineers, and product managers to deliver products.
- Build machine learning models through design, training, evaluation, validation, and implementation.
- Use data and technology to uncover insights and communicate their business relevance.
What they ask for
- Bachelor’s degree in a quantitative field plus 2 years of data analytics experience, or a master’s degree in a quantitative field or an MBA with a quantitative concentration.
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Experience building, validating, and backtesting models; familiarity with techniques including clustering, classification, sentiment analysis, time series, and deep learning.
Nice to have
- STEM master’s degree or PhD.
- Experience with AWS; 2+ years in Python, Scala, or R; 2+ years in machine learning; or 2+ years in SQL.
Pay
$135,600 - $154,800 USD base salary
Tools
Python, Conda, AWS, H2O, Spark, Scala, R, SQL
AI focus
Build, validate, and implement machine learning models, and deploy and modernize the pipelines and platforms that run them.
Model-written summary · the original posting is authoritative