Principal Associate, Data Scientist - Emerging ML

Capital One Capital One · Banking · McLean, VA +2

The role is for a Principal Associate Data Scientist in Capital One's Emerging ML team, focusing on research and development of Embeddings and Foundation Models. The candidate will build ML models from design through training, evaluation, and validation, and partner with engineering to operationalize them for production systems serving over 50 million customers. The role involves working with large datasets (billions of customer transactions) using tools like Spark and AWS, and applying various ML techniques including deep learning, classification, and time series analysis.

What you'd actually do

  1. Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them in scalable and resilient production systems that serve 50+ million customers.
  2. Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.
  3. Write software (Python, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark and AWS.

Skills

Required

  • Python
  • Scala
  • SQL
  • machine learning
  • data analytics

Nice to have

  • Spark
  • AWS
  • clustering
  • classification
  • sentiment analysis
  • time series analysis
  • deep learning

What the JD emphasized

  • operationalize them in scalable and resilient production systems
  • billions of customer transactions

Other signals

  • foundation models
  • embeddings
  • operationalize models
  • customer transactions