Manager, Data Scientist

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

Manager, Data Scientist role focused on model risk management within a fintech company. The role involves partnering with cross-functional teams to identify and quantify model risks, building ML models to challenge existing production models, contributing to model governance, and validating various models. Requires strong statistical and data science skills, experience with ML, and open-source tools.

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. Build machine learning models to challenge “champion models” that are deployed in production today
  3. Contribute to the model governance framework for the next generation of machine learning models
  4. Flex your interpersonal skills to present how model risks could impact the business to executives
  5. Validate a wide variety of models across multiple business domains within our Enterprise Services devision

Skills

Required

  • Bachelor's Degree in a quantitative field or equivalent experience
  • 6 years of experience performing data analytics
  • 1 year of experience leveraging open source programming languages for large scale data analysis
  • 1 year of experience working with machine learning
  • 1 year of experience utilizing relational databases

Nice to have

  • PhD in STEM field
  • 3 years of experience in data analytics
  • 1 year of experience working with AWS
  • 4 years’ experience in Python, Scala, or R for large scale data analysis
  • 4 years’ experience with machine learning
  • 4 years’ experience with SQL
  • 4 years’ experience building or validating models related to fraud detection, digital marketing, cybersecurity, or sensitive data detection.

What the JD emphasized

  • model risks
  • challenge "champion models"
  • model governance framework
  • validate a wide variety of models

Other signals

  • building machine learning models to challenge champion models
  • model governance framework for the next generation of machine learning models
  • validate a wide variety of models across multiple business domains