Senior Manager, Data Analytics (Insurance)

Toronto, ON
Apr 13, 2021

Our client…

One of the world's most recognized consulting companies leading the way in tax, accounting and technology services are looking for a leader in their Data Science and Analytics department.


Must Have:

  • A MSc or Ph.D in Computer Science, Mathematics, Data Science, Data Analytics, or a related field
  • Experience with range of data transformation and modelling tools, for example: SQL, SSIS, SSAS, Azure Data Factory, Informatica, Power Query
  • Experience with range of data visualization tools, for example: Power BI, Tableau, Qlik, SSRS
  • Experience with data virtualization, data automation, data architecture
  • The ability to provide excellent client service and manage and build strong relationships both internally and externally, coupled with a strong interest in further developing and integrating operations with technology skills.
  • Awareness of emerging issues, including regulations, industry practices and new technologies.

Nice to Have:

  • Experience with languages like SQL, DAX, Python and Scala
  • Some exposure to Machine learning concepts (Regression, K-NN, Decision trees…) and tools such as Numpy and Pandas
  • Working experience with more than one of the Cloud Data Platforms (such as Azure, AWS and GCP)



  • Overseeing the direction and work-flow of project work undertaken by the Data Analytics Division including strategic and growth input and assigning projects as appropriate
  • Client-wide and/or company-specific Data modelling, including identifying, designing and developing applications for implementing predictive analytics
  • Identifying and advising of results and their implications to business stakeholders and leadership
  • Identify, recommend, develop, and maintain systems and methodology that support robust predictive models and business tools that address business needs and support business decisions to improve our competitive position.
  • Ensure effective design, development and implementation of statistical predictive models using data mining techniques, testing, scoring, and monitoring
  • In partnership with Information Technology ensure the design and development of big data applications for implementing predictive analytics and machine learning algorithms, with the goal of discovering valuable insights from available data

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