Senior Manager, Data Science - Model Risk Office

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

Senior Manager for Model Risk Office at Capital One, focusing on identifying and quantifying risks associated with models, including Generative AI. The role involves building ML models to challenge existing production models and contributing to the governance framework for future models. It requires validating models across various business domains and communicating risks to executives. The ideal candidate is innovative, creative, a leader, technically proficient, statistically minded, and skilled in handling large datasets.

What you'd actually do

  1. Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
  2. Leverage a broad stack of technologies — from foundational frameworks (PyTorch, Hugging Face), to orchestration tools (LangChain, Vector Databases) to LLMOps, observability platforms, and more — to reveal the insights hidden within huge volumes of multi-modal data
  3. Build machine learning models to challenge “champion models” that are deployed in production today and contribute to the model governance framework for the next generation of models
  4. Validate a wide variety of models across multiple business domains within our Enterprise Services division, and flex your interpersonal skills to present how identified model risks could impact the business to executives.

Skills

Required

  • Bachelor's Degree in a quantitative field plus 7 years of experience performing data analytics OR Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of experience performing data analytics OR PhD in a quantitative field plus 2 years of experience performing data analytics
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis
  • At least 2 years of experience working with machine learning
  • At least 2 years of experience utilizing relational databases

Nice to have

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

What the JD emphasized

  • unique risks associated with Generative AI (GenAI)
  • challenge “champion models” that are deployed in production today
  • present how identified model risks could impact the business to executives

Other signals

  • model risk management
  • challenging production models
  • governance framework
  • Generative AI risks