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Principal Associate, Data Scientist
Capital OneData Scientist on Card Payment Fraud Prevention team at Capital One. Building and deploying machine learning models to enhance customer safety and reduce fraud losses across millions of transactions.
Posted 7/31/2026full-timeMcLean • Illinois, New York, Virginia • 🇺🇸 United StatesJuniorMid-Level💰 $147,100 - $201,400 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying machine learning models, leveraging technologies such as Python and AWS, while ensuring compliance and managing model risk. Collaborates effectively with cross-functional teams to deliver data-driven insights and maintain production data science solutions.
Highest-signal resume keywords
Machine Learning Model DevelopmentPython ProgrammingAWS ExperienceData AnalyticsModel Risk Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData AnalyticsPythonSQLSparkScalaRModel Risk ManagementGenAI TechniquesTechnical Documentation
Soft Skills
CollaborationTeam LeadershipCommunication
Tools & Technologies
AWSH2OCondaSpark
Industry Keywords
Quantitative FieldRegulatory ComplianceBig DataDistributed Computing
Tech Stack
Tools & technologiesAWSPythonScalaSparkSQL
About the role
Key responsibilities & impact- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights hidden within large volumes of numeric and textual data
- Build machine learning models from design through training, evaluation, validation, and implementation, monitoring and supporting continuous model deployment and maintenance
- Collaborate on the design and maintenance of production data science solutions, including writing clear technical documentation and ensuring models adhere to software development best practices
- Manage model risk and maintain regulatory compliance across the model lifecycle
Requirements
What you’ll need- Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or higher
- 5 years of experience performing data analytics (or 3 years with Master’s degree or 3 years with PhD)
- At least 1 year of experience working with AWS
- At least 3 years’ experience in Python, Scala, or R
- At least 3 years’ experience with machine learning
- At least 3 years’ experience with SQL
- Experience with big data and distributed computing, using Spark or another comparable framework
- Experience with model risk governance
- Experience technically leading and developing a team
- Experience with both traditional machine learning and emerging GenAI techniques, focusing primarily on traditional ML model development
Benefits
Comp & perks- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Performance-based incentive compensation (including cash bonuses and/or long-term incentives)
- Comprehensive, competitive, and inclusive set of health, financial and other benefits