Predictive Modeller

  • 34907
  • Non-Life - Actuarial
  • |
  • Ontario, Canada
  • |
  • Mar 19, 2019
  • You will gain exposure to all aspects of insurance operations with respect to claims, underwriting and pricing, as well as general areas of business operations such as human resources and marketing, working on high impact actionable projects.
  • You will learn the business knowledge of the prospective stakeholder through their information datasets.
  • Combining quantitative data with business domain knowledge, you will transform them into predictive models that provide insights that ultimately produce new and creative analytic solutions as part of our core deliverables.
  • You will work hand in hand with data scientists, business stakeholders in developing models and identifying strategies to improve the company’s bottom line.
  • BSc or M. Sc. in Operation Research, Applied Statistics, Actuarial Science, Computer Science Data Mining, Machine Learning, Physics or related quantitative discipline or equivalent.
  • 3 - 5 years of using statistical analysis or models to make forecasts or predictions, preferably working with large datasets.
  • Creative, inquisitive, comfortable with vague guidelines and able to learn quickly and independently.
  • Curious about data and passionate about the business, and able to communicate ideas to a wide range of audience with different knowledge backgrounds.
  • Understanding of various modeling techniques and when it is most appropriate to apply them. Functional knowledge of machine learning algorithms is an asset.
  • Able to choose the right model and optimize parameter selections and explain the rationale for the selection, especially for GLM models.
  • Knowledge of how to prepare data in the framework of a predictive modelling problem is required.
  • Fluent in SAS, Python, R and SQL, knowledge of, Java or VBA would be an asset.
  • Experience with ML frameworks/libraries e.g. Scikit-learn, Pandas, Matplotlib, Seaborn, Tensorflow or Pytorch would be an asset.