Data Scientist

  • 35504
  • Non-Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Jul 17, 2019
Insurance
RESPONSIBILITIES
  • Provide data support to Claims business inclusive of data mining, automated reporting and modelling.
  • Transformation of complex data sets into meaningful conclusions & recommendations.
  • Develop innovative solutions for pattern recognition using machine learning and statistical approaches.
  • Maintenance of expanding set of data mining tools, frameworks & approaches.
  • Communicate actionable recommendations based on insights/model results.
  • Deliver proactive analysis on CAT exposure, historical performance and decision making using weather and geo-analytical approaches.
  • Driving co-ordination/delivery accountability of project and BAU delivery based on timelines & direction.
  • Driving conformance/Alignment to IT/Enterprise Architecture standards.
QUALIFICATIONS
  • Highly numerate, you will be educated to post graduate in a relevant discipline; Mathematics, Statistics, Computer Science.
  • You will bring solid experience in a related role with a record of accomplishment of solving complex non-routine problems; along with expertise in some, if not all, of the following areas: Statistics, Machine Learning, Deep Learning & AI.
  • You will have experience at all stages of data science; problem definition, data acquisition & wrangling, modelling, feature engineering and deployment.
  • Big Data experience would be ideal, but not essential.
  • Programming knowledge and a gift for coding using: R, Python or Spark.
  • Your knowledge must also come with the ability to explain technical concepts to non-specialists.
  • You will also need the drive to deliver projects, leading teams and coaching development.
  • You will be equipped to provide insights and deployments at scale.
  • You thrive on complex, non-routine problems.
  • Primary Skillsets:
  • Python/R /Dataiku.
  • REST/XML/JSON/API ingestión.
  • Spark/Impala/Hive.
  • Expertise in machine learning theory and predictive modelling lifecycle.
  • API configuration.
  • Conformance/Alignment to IT/Enterprise Architecture standards.
  • Relevant experience in P&C.
  • Shiny App development.
  • Geo-analytics experience with specialization in weather & environmental data ingestion.