Principal Associate, Data Scientist - US Card (generative AI Systems)

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

This role is for a Principal Associate Data Scientist on the Generative AI Systems (Genesis) team within Capital One's Card Data Science division. The team builds state-of-the-art generative AI solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing. The role involves partnering with cross-functional teams to deliver customer-facing and internal applications, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, innovative, creative, technically proficient, statistically-minded, and adept at handling large datasets.

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

  • Python
  • AWS
  • Spark
  • SQL
  • machine learning
  • quantitative field degree (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science)
  • data analytics experience

Nice to have

  • Master’s Degree in STEM
  • Scala
  • R
  • H2O
  • Condo

What the JD emphasized

  • state-of-art, generative AI-based solutions
  • customer-facing applications
  • experimenting with emerging technologies in generative AI
  • delivering software implementing these technologies
  • contributing research to major NLP and AI/ML conferences
  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

Other signals

  • Generative AI Systems
  • dialogue, text summarization, reading comprehension, speech recognition, image/document processing
  • customer-facing applications
  • internal applications
  • experimenting with emerging technologies in generative AI
  • delivering software implementing these technologies
  • contributing research to major NLP and AI/ML conferences