Director, Data Scientist - External Data Strategy

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

This role is for a Director of Data Science focused on External Data Strategy within Capital One's fintech domain. The position involves leading a team of 10-15 data scientists, building machine learning models and data pipelines, and leveraging technologies like Python, Spark, Databricks, and AWS. The primary focus is on data lifecycle management, from sourcing to feature engineering and model implementation, to understand customer financial lives and drive business decisions. The role requires strong leadership, technical expertise in data science and machine learning, and experience with large-scale data analysis and relational databases.

What you'd actually do

  1. Lead a team of 10-15 data scientists as a leader-of-leaders by setting a strategic agenda, providing technical oversight and guidance, and developing talented individual contributors and managers.
  2. Build machine learning models and data pipelines through all phases of development, from design through training, evaluation, validation, and implementation
  3. Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver data and insights that drive the business
  4. Develop deep subject matter expertise in consumer financial data and how that data enables Capital One to make the right decisions for our customers.
  5. Leverage a broad stack of technologies — Python, Conda, AWS, Databricks, Spark, and more — to reveal the insights hidden within huge volumes of data

Skills

Required

  • Bachelor's Degree in a quantitative field or equivalent experience
  • Master's Degree in a quantitative field or MBA with quantitative concentration or equivalent experience
  • PHD in a quantitative field or equivalent experience
  • 4 years of experience leveraging open source programming languages for large scale data analysis
  • 4 years of experience working with machine learning
  • 4 years of experience utilizing relational databases

Nice to have

  • 3 years of experience working with AWS
  • 3 years of experience managing people
  • 5 years of experience in Python for large scale data analysis
  • 5 years of experience with machine learning
  • 5 years experience with Spark

What the JD emphasized

  • machine learning
  • data pipelines
  • data analytics

Other signals

  • building machine learning models
  • data pipelines
  • advanced analytics