• 38558
  • Non-Life - Actuarial
  • |
  • Illinois, United States
  • |
  • Nov 9, 2020
  • Build and evaluate pricing models and risk segmentation plans.
  • Enhance evaluation pipelines to translate model results into KPIs.
  • Leverage internal and external data sources to engineer novel features to enhance risk segmentation.
  • Build data processing pipelines to quickly iterate on research ideas and put them into production.
  • Take end-to-end ownership of problem domains and continuously improving upon quantitative solutions.
  • Advanced degree in a quantitative discipline and/or 3+ years of applying advanced quantitative techniques to problems in industry.
  • Actuarial pricing experience preferred.
  • Strong demonstrable knowledge of topics such as Bayesian statistics, machine learning, and numerical optimization.
  • Exceptional communicator and storyteller.
  • Strong programming skills with experience using modern packages in R and Python.
  • Demonstrated experience building, validating, and applying statistical machine learning methods to real world problems.