Senior Associate, Data Scientist - Business Cards & Payments Credit Infrastructure Team

Capital One Capital One · Banking · McLean, VA

Capital One is seeking a Senior Associate Data Scientist to join their Business Cards & Payments Credit Infrastructure Team. This role will focus on developing and implementing valuations models and advanced analytics for credit card acquisitions. The data scientist will partner with cross-functional teams, leverage technologies like Python, AWS, and Spark, and build machine learning models through all phases of development. The ideal candidate has a strong statistical background, experience with various ML techniques, and is comfortable with open-source tools and cloud platforms.

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 (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
  • Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration

Nice to have

  • Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
  • At least 1 year of experience working with AWS
  • At least 2 years of experience in Python, Scala, or R
  • At least 2 years of experience with machine learning
  • At least 2 years of experience with SQL

What the JD emphasized

  • machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

Other signals

  • credit card acquisitions valuations model development
  • machine learning technologies
  • billions of customer records