Senior Manager, Data Scientist -retail Bank Data Science Experimentation Lead

Capital One Capital One · Banking · McLean, VA

This role leads the Design of Experiments (DoE) and Causal Inference center of excellence within Retail Bank Data Science. The primary focus is on standardizing experimental design, measuring incrementality, and applying causal inference techniques to validate product initiatives and business assumptions before full-scale development. The role involves building experimental infrastructure, consulting on advanced techniques, and partnering with cross-functional teams to deliver data-driven insights for financial products.

What you'd actually do

  1. Standardize how we measure incrementality across the organization to ensure metric improvements are tied to specific, isolated initiatives, reducing misattribution.
  2. Work with Product Managers and Business Analysts to design in-market tests early in the lifecycle, validating high-risk assumptions before full-scale development.
  3. Build the infrastructure for testing, including a centralized repository for hypotheses, known covariates, causal models, and results.
  4. Consult with Data Scientists and Analysts on advanced causal inference techniques for observational data where A/B testing isn't feasible.
  5. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.

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

  • rigorous testing
  • experimental design
  • causal inference techniques
  • closed-loop experimental frameworks