Job Description

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Hiring Unit:

Desautels Faculty of Management

Course Title and Course Number:
Data-Driven Models for Operations Analytics MGSC 416

Estimated Number of Positions:

1

Total Hours of Work per Term:

45

Position Summary:Support the instructor in course redesign and updates to reflect advances in AI-driven analytics and LLM-assisted teaching (e.g., improving examples, automating feedback, and enhancing case study materials). Assist in the preparation and streamlining of Python-based materials, including notebooks, assignments, and grading scripts. Help modernize homework assignments and project guidelines to incorporate responsible AI usage in data analytics. Provide tutorial sessions or office hours to assist students with Python, optimization modeling, and data analysis. Assist in grading assignments, projects, and exams following course rubrics. Provide feedback and guidance to student teams working on data-driven projects.

Qualifications:Graduate student (MSc or PhD) in Management, Analytics, Operations, or a related field. Strong programming skills in Python (NumPy, Pandas, Gurobi), R would be a plus. Experience or strong interest in AI/LLM applications in data science or teaching contexts. Familiarity with operations analytics, optimization, and case-based teaching. Prior TA or teaching experience is an asset.

Hourly Salary:
$37.34
Position Start Date:
2026-01-04
Position End Date:
2026-04-18
Deadline to Apply:McGill University hires on the basis of merit and is strongly committed to equity and diversity within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities. McGill implements an employment equity program and encourages members of designated groups to self-identify. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence, accessibilityrequest.hr@mcgill.ca.