Data Scientist

  • 36776
  • Non-Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Feb 10, 2020
  • You will work on impactful projects that range from predicting customer life-time values and optimizing customer journeys to incorporating novel data sources for building cutting-edge pricing algorithms.
  • You will leverage machine-learning algorithms to automate and predict claim outcomes and find new and innovative ways to impact our customers.
  • You will be part of a dynamic small team with exposure to different business partners and direct influence on future products and innovative solutions.
  • You will propose machine-learning and statistical models for practical applications that impacts millions of customers.
  • You will also mentor and guide your peers in novel approaches and provide peer review for their work.
  • An educational background in computer-science or engineering, math, statistics, physics or related field. A minimum of MSc is required and PhD preferred.
  • 5+ years of experience with model development and working with large datasets. This can include experience from any industry or academia.
  • 5+ programming experience in Python or R with good grasp of software engineering standard methodologies such as code-reusability, modularity, use of repos, etc.
  • A growth mindset with versatile skills and able to work through problems from first-principles.
  • A portfolio of projects that demonstrate your ability to draw inferences from data. This includes participation within the broader data science community including Kaggle competitions or a0ny personal projects with open data.
  • A can-do teammate who is willing to roll-up the sleeves and do whatever is needed to move projects forward. That means at times you will wear different hats and be a project manager, developer, modeler and chief communicator of solutions.
  • Amazing people skills and able to translate and communicate complex algorithms to non-technical individuals.
  • Creative, self-motivated and can lead projects independently.