Data Scientist

  • 34569
  • Non-Life - Data Science
  • |
  • Manitoba, Canada
  • |
  • Jan 23, 2019
  • Work with various stakeholder to translate business questions into formalized and repeatable analytical processes.
  • Work with various stakeholders throughout the organization to design, develop, and assess experiments aimed at uncovering meaningful and actionable insights.
  • Disseminate the findings from analysis and experiments for easier stakeholder consumption.
  • Assist in the development and refinement of measures and reports designed to improve decision making.
  • Document all aspects of the analytical process, including data requirements, data processing, analytical approaches utilized, any created code and, in general, the findings of the work conducted.
  • Contribute to educational initiatives aimed at the development of overall inter- and intra-departmental knowledge.
  • Contribute to data management improvements.
  • Follow established practices, processes and guidelines.
  • Keep up to date on current statistical and mathematical models and methodologies, including those relating to machine learning, deep learning, and artificial intelligence.
  • Perform other duties as assigned.
  • Completion of post-secondary degree/certificate preferably in the area of computer science, mathematics, statistics, actuarial science/mathematics, engineering, physics, or other related field.
  • Academic or practical experience performing analysis or developing analytical processes using current programming languages and/or statistical software.
  • Academic or practical experience performing data exploration, data management, and other data related activities.
  • Detail oriented with analytical and problem-solving skills and an ability to recognize and identify issues and take proper action to resolve them.
  • Effective communication skills, with the ability to communicate in a clear and concise manner with style fitting for the audience and message.
  • Effective organizing skills with the ability to self-manage a fluctuating workload, with various situations and changing priorities.
  • Effective collaboration skills, with the ability to work in a team setting by making contributions and supporting team members.
  • Experience with analytical tools such as Python and R is considered an asset.
  • Knowledge and experience in the insurance industry is considered an asset.