Director, Data Science

Capital One Capital One · Banking · Toronto, ON

Director of Data Science at Capital One Canada, responsible for managing the risk and uncertainty in statistical models, leading the architecture and development of ML models through all phases, and leveraging technologies like Python and AWS, including agentic AI. The role involves managing talent and investigating new technologies for digital banking.

What you'd actually do

  1. Partner with a cross-functional team of data practitioners, software engineers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions, not just avoid the worst ones.
  2. Leverage a broad stack of technologies — Python, AWS, agentic AI, and more — to reveal the insights hidden within huge volumes of numeric and textual data
  3. Lead the architecture and development of machine learning models through all phases of development, from design through training, evaluation, and implementation
  4. Flex your interpersonal skills to translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities
  5. Manage and develop talent to drive a highly performant and engaged team

Skills

Required

  • Bachelor’s Degree plus 9 years of experience in data analytics, or Master’s Degree plus 7 years of experience in data analytics, or PhD plus 5 years of experience in data analytics
  • At least 4 years of experience in open source programming languages for large scale data analysis
  • At least 4 years of experience with machine learning
  • At least 4 years of experience with relational databases

Nice to have

  • PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
  • At least 5 years’ experience working with or developing data science/machine learning solutions
  • At least 1 year of experience working with AWS
  • At least 3 years of experience managing people
  • At least 5 years of experience in Python, Scala, or R for large scale data analysis

What the JD emphasized

  • manage the risk and uncertainty inherent in statistical models
  • architecture and development of machine learning models
  • Manage and develop talent

Other signals

  • manage the risk and uncertainty inherent in statistical models
  • architecture and development of machine learning models
  • investigating the impact of new technologies on the future of digital banking