Manager, Data Scientist - Bureau Data Strategy

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

Capital One is seeking a Manager, Data Scientist for their Bureau Data Strategy team. This role involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark to analyze large datasets, and building machine learning models through all phases of development. The ideal candidate is customer-focused, a leader, technically proficient with open-source tools and cloud platforms, and skilled in data analysis.

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 SQL

What the JD emphasized

  • machine learning models through all phases of development
  • huge volumes of numeric and textual data
  • At least 1 year of experience working with machine learning
  • At least 4 years’ experience with machine learning

Other signals

  • build machine learning models through all phases of development
  • delivering insights from large volumes of numeric and textual data
  • shaping the future of how credit bureau data is used in underwriting