Data science, math and statistics co-op

by | Programs


Common types of co-op work

  • Academic research (Theoretical and applied)
  • Data analysis
  • Software development / software engineering
  • Mathematical modelling
  • Control statistics
  • Logistics
  • Outreach and education
  • Government and policy
  • Natural resource management
  • Health research and and Health information systems
  • Geographic information systems
  • Communications
  • Medical statistics and biostatistics
  • Finance and actuary related work

Sample co-op positions and employers

  • Junior Analyst—BC Ministry of Health (Health Sector Information, Analysis and Reporting)
  • Environmental assessment co-op student—Environment and Climate Change Canada
  • Investment operations intern—BC Investment Management Corp.
  • Junior developer—Workday (MediaCore)
  • Modelling and analytics support technician—Alberta Environment and Parks
  • Quality assurance analyst co-op student—RevenueWire
  • STEM outreach assistant—African Institute for Mathematical Sciences
  • Student research assistant in bioinformatics—Agriculture and Agri-Food Canada
  • Survey methodology co-op student—Statistics Canada
  • Toronto investments analyst—Manulife Financial

Knowledge you can gain on your work term

Logic and critical thinking

  • work with abstract reasoning and be able to make ideas precise by formulating them mathematically or statistically
  • analyze, test, and interpret technical arguments, and form independent judgements

Problem solving

  • use mathematics and statistics to help guide possible lines of inquiry
  • solve complex problems by dividing them into simpler sub-problems
  • gather and organize relevant qualitative and quantitative information
  • sharpen or focus mathematical or statistical questions as a problem-solving strategy
  • identify and assess methods of analysis
  • construct abstract models using mathematical and statistical tools
  • use computers and software
  • engage your creativity in the quest for novel solutions
  • document problem-solving steps and reliably certify the validity of your methods and results
  • interpret and evaluate

Communication

  • work effectively in a multi-disciplinary environment
  • accept comments and feedback, and learn from them
  • explain mathematical or statistical concepts to non-experts
  • justify choices made during problem solving and interpretation of results
  • present the results and assessment of a problem-solving strategy
  • clearly communicate logical arguments to a range of audiences

Mathematical, statistical and numerical literacy

  • recognize the value of mathematical and statistical thinking, training and approach to problem solving
  • be familiar with how mathematics or statistics helps accurately explain abstract or physical phenomena
  • recognize and appreciate the connections between theory and applications
  • read mathematical and statistical literature, including survey articles, scholarly books, and online sources
  • be able to independently expand your mathematical or statistical expertise