Senior Manager, Data Science

Capital One Capital One · Banking · Toronto, ON

Senior Manager, Data Science role at Capital One Canada, focusing on leading the development and operationalization of data pipelines, machine learning models, and tools to leverage AWS for data-driven decision-making in financial services. The role involves managing talent, exploring data sources, and optimizing business programs.

What you'd actually do

  1. Overseeing the development of software to operationalize, clean, and investigate large, messy data sets of structured and unstructured data
  2. Networking with various teams to explore internal and external data sources and APIs to help uncover new trends and improve analysis
  3. Designing and contributing to highly scalable data pipelines, machine learning models, tools, and products to enable the analyst community to fully leverage the power of AWS
  4. Managing and developing talent to drive a highly performant and engaged team
  5. Working with various teams to analyze large swaths of data in order to optimize various business programs

Skills

Required

  • Python
  • Scala
  • Java
  • Git
  • GitHub
  • SQL
  • machine learning workflows

Nice to have

  • AWS
  • EC2
  • S3
  • Lambda
  • RDS
  • CICD tools
  • advanced Git Workflows

What the JD emphasized

  • At least 7 years of experience in open source programming languages for large scale data analysis (Python, Scala, or Java)
  • At least 7 years of experience with version control system like Git and GitHub.
  • At least 7 years of experience with relational databases and programming in SQL
  • At least 4 years in lead positions (managing people/owning products/architecting and driving an agenda)
  • At least 2 years of experience with machine learning workflows

Other signals

  • leading the next wave of disruption at a whole new scale
  • operating across billions and billions of customer transactions
  • unlocking big opportunities that help everyday people save money, time, and agony in their financial lives
  • Designing and contributing to highly scalable data pipelines, machine learning models, tools, and products to enable the analyst community to fully leverage the power of AWS
  • Managing and developing talent to drive a highly performant and engaged team