Manager, Data Scientist - US Card Dfs Acquisitions

Capital One Capital One · Banking · Riverwoods, IL +2

Manager, Data Scientist role focused on building and deploying machine learning models for credit card customer acquisitions in the fintech domain. The role involves the full model lifecycle, from design and training to evaluation, validation, and implementation, with a focus on delivering customer-facing products.

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 plus 6 years of experience performing data analytics OR Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of experience performing data analytics OR PhD in a quantitative field plus 1 year of experience performing data analytics
  • At least 1 year of experience leveraging open source programming languages for large scale data analysis
  • At least 1 year of experience working with machine learning
  • At least 1 year of experience utilizing relational databases

Nice to have

  • PhD in “STEM” field plus 3 years of experience in data analytics
  • At least 1 year of experience working with AWS
  • At least 4 years’ experience in Python, Scala, or R for large scale data analysis
  • At least 4 years’ experience with machine learning
  • At least 4 years’ experience with SQL

What the JD emphasized

  • model risk standards
  • full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases

Other signals

  • builds industry leading machine learning models
  • own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases
  • deliver the solutions from ideation to implementation