Senior Data Scientist

  • 39080
  • Non-Life - Data Science
  • |
  • Alberta, Canada
  • |
  • Feb 9, 2021
Insurance
RESPONSIBILITIES
  • Use the latest Cloud platforms to create applications/forecasting reports AWS, Azure, Databricks.
  • Research, development, interpretation and deployment of machine learning and predictive models - all with an eye to understanding and predicting member behaviour.
  • Use data insights to drive decision-making at the organizational level.
  • Combine programming and analytical skills to support a consistent member experience across the business units.
  • Realize operational and marketing efficiencies and identify opportunities for improvement.
  • Present member insights to staff in support of the company’s strategic direction and tactics.
  • Anticipate analytic opportunities, with the goal of deepening and growing our understanding of company’s member base.
  • Validate the company’s use of machine learning, developing processes and tools to monitor outcomes and analyze model performance.
  • Analyze member engagement and make recommendations for next-best offers.
  • Support responsible and targeted outbound marketing through the optimization of product development and strategy.
  • Deepen the company’s A/B testing approach and framework.
  • Help define complex problems as they arise, using advanced analytics and research techniques.
  • Lead short and long-term forecasting to drive agility in decision-making.
  • Data governance, including the leveraging of version-control in analysis, model development and deployment.
  • Engage in validation and peer review, back-testing against known measures.
  • Consult with stakeholders to deliver analytic value on an operational and ad hoc basis.
QUALIFICATIONS
  • You have your Bachelor’s or Master’s (Preferred) degree in computer science, mathematics, statistics, or a related quantitative field.
  • You have at least three years’ employment experience in data science, predictive modelling or machine learning areas.
  • You have strong problem-solving and organizational skills.
  • You’re a whiz at applying machine learning algorithms - GLM, GAM, Decision Tree, Random Forest, Boosting, Text Mining and more.
  • Your job experience is rich with product development know-how.
  • You’re fluent in statistical programming languages - especially R and Python.
  • Your expertise in Deep Learning and Unsupervised techniques such as clustering, autoencoders make you stand out.
  • You’re familiar with relational databases, such as SQL. You get bonus points if you also have experience with distributed computing frameworks such as Spark and Hadoop.
  • You’re experienced in Natural language processing such as classification, sentiment analysis, and topic modeling
  • You’re experienced in Cloud platforms such as AWS, Azure, Google Platform or Databricks.
  • You understand data and know how to apply different models to different business platforms.