Data Scientist

  • 37756
  • Non-Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Jun 21, 2019
  • 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.
  • Will work hand in hand with data scientists, business stakeholders in developing models and identifying strategies to improve the company’s bottom line.
  • Minimum of 2 - 3 years of Machine Learning and analytics experience within a professional services firm or similar industrial environment.
  • Bachelor's degree or higher from an accredited college in a Mathematics, Statistics, Actuarial Sciences, Computer Science, Physics, Engineering or a related field .
  • Extensive experience in Machine learning algorithms, model implementation and optimization to solve Regression, Classification and Segmentation problems.
  • 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, Tensor flow or Pytorch would be an asset.
  • Business and analytics acumen to run and interpret the results of models - turn large amounts of complex, detailed information into clear summaries and business recommendations.
  • Excellent collaboration skills and the ability to work in a team environment and across multiple sites and business units.
  • Excellent communication and interpersonal skills - be able to effectively communicate complex results to a business audience not familiar with complex data and analytics.
  • Nice to have:
  • Experience working with NLP or NLU related problems, topic modelling, and event discovery and sentiment analysis.
  • Functional knowledge of working with open source using Python, Git and Hadoop stack.