Senior Manager, Data Scientist - Card Dfs Integration

Capital One Capital One · Banking · McLean, VA

This role is for a Senior Manager, Data Scientist focused on Card DFS Integration within Capital One's Discover Card Customer Management Data Science team. The role involves partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building machine learning models through all phases of development. The ideal candidate is customer-focused, creative, statistically-minded, and proficient with large datasets and various machine learning techniques including clustering, classification, sentiment analysis, time series, and deep learning.

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

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

  • delivering a product customers love
  • huge volumes of numeric and textual data
  • design through training, evaluation, validation, and implementation
  • translate the complexity
  • Customer first
  • Statistically-minded
  • A data guru

Other signals

  • building machine learning models
  • design through training, evaluation, validation, and implementation
  • experience with clustering, classification, sentiment analysis, time series, and deep learning