Senior Manager, Data Science, Bank Operations

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

Senior Manager, Data Science for Bank Operations at Capital One. This role involves building machine learning models for core internal capabilities like Check/Document Reading, Anomaly Identification, NLP of Calls, and operational forecasting, utilizing technologies such as neural networks, LLMs, and transformer architectures. The candidate will partner with cross-functional teams, leverage technologies like Python, AWS, H2O, and Spark, and manage the full lifecycle of ML model development.

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 or equivalent experience
  • 7 years of experience performing data analytics
  • 2 years of experience leveraging open source programming languages for large scale data analysis
  • 2 years of experience working with machine learning
  • 2 years of experience utilizing relational databases

Nice to have

  • PhD in STEM field
  • 4 years of experience in data analytics
  • 1 year of experience working with AWS
  • 1 year of experience managing people
  • 5 years’ experience in Python, Scala, or R for large scale data analysis
  • 5 years’ experience with machine learning

What the JD emphasized

  • machine learning models
  • neural networks
  • LLMs
  • transformer architectures
  • agentic experiences
  • open-source languages
  • data science solutions
  • open-source tools
  • cloud computing platforms

Other signals

  • build machine learning models through all phases of development
  • emerging technologies like neural networks, LLMs, transformer architectures
  • operational forecasting
  • Check/Document Reading
  • Anomaly Identification
  • Natural Language Processing of Calls