Data Literacy TA (Online/Zoom)

McGill University

Montreal

On-site

CAD 52,000 - 58,000

Part time

3 days ago
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Job summary

McGill University's Department of Global and Public Health is seeking a Course Assistant for Data Literacy (GPHL 300) in Montreal. The role supports course delivery by meeting supervisors, clarifying assignments, attending Zoom lectures, and assisting with grading and online management.

Ideal candidates are a PhD candidate or 2nd-year Master’s student, highly organized with attention to detail, and able to help students develop data-driven reasoning and interpret datasets within real-world

Qualifications

  • PhD candidate or 2nd-year Master’s student required.
  • Organized with strong time management.
  • Attention to detail across course aspects.
  • Approachable and helpful in student support.
  • Familiar with course materials and assignments.
  • Background in data literacy concepts, statistics, data viz and epidemiology basics.
  • Able to support students in data-driven reasoning and graph interpretation.

Responsibilities

  • Meet periodically with course supervisors.
  • Clarify course content and assignments with students.
  • Attend regular Zoom lectures.
  • Assist with evaluation/grading.
  • Assist with online course management.
  • Help prepare and facilitate class discussions, media sharing, and group work.
  • Uphold academic integrity and communicate concerns with course supervisors.
  • Respond to or share email communications from students with course supervisors as appropriate.

Skills

Organized
Time management
Attention to detail
Data literacy background
Communication

Education

PhD candidate or 2nd-year Master’s student

Job description

McGill University's Department of Global and Public Health is seeking a Course Assistant for Data Literacy (GPHL 300) in Montreal. The role supports course delivery by meeting supervisors, clarifying assignments, attending Zoom lectures, and assisting with grading and online management.

Ideal candidates are a PhD candidate or 2nd-year Master’s student, highly organized with attention to detail, and able to help students develop data-driven reasoning and interpret datasets within real-world

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