Senior Data Scientist

  • 33488
  • Non-Life - Other
  • |
  • Ontario, Canada
  • |
  • Apr 5, 2018
Insurance
RESPONSIBILITIES
  • Lead all aspects of a modeling engagement, including design, development, validation, calibration, and documentation, and approval, implementation, monitoring, and reporting.
  • Serve as a Subject Matter Expert for predictive modeling with business users; consult with the business, as appropriate, on predictive modeling solutions.
  • Engage internal clients to identify their business needs and develop, implement, and manage solutions.
  • Establish and maintain strong relationships with key business stakeholders.
  • Research complex business issues and recommend solutions, including model inputs through to end product.
  • Validate the performance of existing quantitative risk models and recommend changes when necessary.
  • Develop a solid working knowledge of how current systems and data sources are used in existing predictive modeling projects.
  • Develop algorithms that meet business needs.
  • Manage multiple assignments, many of which with challenging timelines.
  • Work independently, as well as collaborate effectively in a team environment.
QUALIFICATIONS
  • Master’s degree with concentration in a quantitative discipline such as (Math/Stat, Economics, Computer Science, Finance, Actuarial Science, etc.).
  • 3 years of applicable experience in predictive analytics.
  • Experience developing logistic regression models and applying modern machine learning techniques.
  • Strong programming skills with the ability to conduct research utilizing Python and SAS to manipulate data and conduct statistical analysis.
  • Strong ability to effectively interpret data and modeling results and draw actionable insights.
  • Ability to effectively communicate complex ideas to both a technical and non-technical audience.
  • Strong knowledge of MS office tools.
  • Creative and inquisitive in nature, flexibility to learn and apply new methodologies.
  • Experience working with very large datasets.
  • Strong technical writing skills.
  • Strong collaboration skills, including the ability to build and maintain relationships with clients.
  • Excellent interpersonal and communication skills.
  • Organized, self-motivated, results-orientated, and resourceful.
  • Strong business acumen, especially in Financial Services Industry Experience in underwriting, risk, statistical modeling roles.