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Data Scientists at from CN

The direct contact would be Mark Mersereau  mark.mersereau@cn.ca


CN is seeking a broadly capable Data Analyst or Data Scientist to join our team. The Individual in this role is expected to be a visionary that exploits the relationships between large datasets to identify, trends, early failure prediction, productivity and safety enhancement.  Firm understanding of statistical processes and tools as well as the ability to query several databases is a must.  The ideal candidate will have a broad understanding of railroad operations and a passion for identifying and answering questions that help CN achieve greater safety and performance levels.  The candidate will be expected to teach and communicate with a multifunction team that will confirm, assist and implement the opportunities that are identified.

  • Work closely with asset management and mechanical teams to identify opportunities.
  • Identify trends, performance or safety opportunities by using rigorous statistical techniques on large data sets.
  • Communicate findings to team and management at all levels.
  • Drive the collection of new data and the refinement of existing data resources.
  • Analyze and interpret the results from analytical tools and be able to explain the meaning to all levels that will interact with this position.
  • Develop best practices for instrumentation and experimentation and communicate those to team members.


  • M.S. or Ph.D. in applied mathematics discipline, statistics or mathematics.  Experience in a relevant role will be considered with verified examples of problem solving and improvement.
  • Worked in a railroad or transportation environment that is sensitive to logistical challenges.
  • Extensive experience solving analytical problems using quantitative approaches.
  • Highly skilled at manipulating and analyzing complex, high-volume data from varying sources.  Primary data source is SAP.
  • A strong passion for empirical research and inquisitive mindset towards answering hard questions with data.
  • A flexible analytic approach that allows for results at varying levels of precision.
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
  • Expert knowledge of an analysis tool such as R, Matlab, or SAS or equivalent.