Actuarial Analyst II

  • 38338
  • Non-Life - Data Science
  • |
  • Manitoba, Canada
  • |
  • Oct 8, 2020
Insurance
RESPONSIBILITIES
  • Work with various stakeholders 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.
  • Participate in planning activities.
  • Contribute to data management improvements.
  • Improve upon and ensure adherence to 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.
  • Mentor other actuarial analysts.
  • Perform other duties as assigned.
QUALIFICATIONS
  • University degree in Actuarial Mathematics, Statistics, Mathematics or other related field of study.
  • Pursuing ACAS or FCAS designation with minimum of 3 Associateship Exams & VEE Credits.
  • Prior work experience in insurance or related field is an asset.
  • Detail oriented with analytical and problem-solving skills and an ability to recognize and identify issues and take proper action to resolve them.
  • Strong creativity skills, with the ability to develop solutions to a variety of problems.
  • Excellent communication skills, with the ability to communicate in a clear and concise manner with style fitting for the audience and message.
  • Strong planning and organizing skills, with the ability to develop and implement plans by prioritizing.
  • Experience with analytical tools such as Python and R is considered an asset.