Principal Associate, Data Scientist - Card Intelligence

Capital One Capital One · Banking · McLean, VA +1

This role is for a Principal Associate Data Scientist focused on Card Intelligence within Capital One's US Card Data Science organization. The role involves building and deploying sophisticated machine learning models across the credit card lifecycle (marketing, acquisitions, underwriting, fraud prevention) to drive business strategy and deliver customer experiences. The candidate will leverage technologies like Python, AWS, and Spark to analyze large datasets, build ML models through all development phases, and translate complex work into tangible business goals. The role emphasizes customer focus, innovation, creativity, leadership, technical proficiency, and statistical expertise.

What you'd actually do

  1. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
  2. Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
  3. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
  4. Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Skills

Required

  • Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 5 years of experience performing data analytics OR Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 3 years of experience performing data analytics OR PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
  • Python
  • SQL

Nice to have

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
  • AWS
  • Scala
  • R
  • machine learning
  • clustering
  • classification
  • sentiment analysis
  • time series
  • deep learning

What the JD emphasized

  • quantitative field
  • data analytics
  • machine learning
  • SQL

Other signals

  • builds and deploys sophisticated data science and machine learning models
  • across the entire credit card lifecycle—including marketing, acquisitions, underwriting, and fraud prevention
  • turn complex insights into real-world impact
  • shaping financial products that serve and protect millions of cardholders daily