Course Lecturer (MGSC 401 001)

McGill Faculty of Medicine and Health Sciences; Montreal (administrative region); On-site; CAD 11,000 - 13,000; Part time

Job summary

McGill University seeks qualified instructors to teach Statistical Foundations of Data Analytics (MGSC 401 001) at ARMST 075 for Winter 2027. The assignment runs Mondays from 8:35 to 11:25 and spans January 5 to April 14, 2027, with a total of 39 class hours and a 3-credit load.

Applicants should hold a PhD/Master's/Bachelor's in Business with hands-on data analytics and machine learning experience, plus university teaching experience.

Qualifications

• PhD, Master's, or Bachelor's in Business with ample experience in data analytics courses and machine learning.
• Fluency in AI algorithms, R-studio, statistical learning, and a teaching track record in these topics.
• University teaching experience required.

Responsibilities

• Teach Statistical Foundations of Data Analytics MGSC 401 001 in ARMST 075 on Mondays 8:35–11:25.
• Prepare and deliver lectures, assignments, and assessments.
• Contribute to course materials and student evaluation.

Skills

AI algorithms

R-studio

Statistical learning

Teaching track record

Education

PhD in Business

Master's in Business

Bachelor's in Business

Job description

Please refer to the How to Apply for a Job (for External Candidates) job aid for instructions on how to apply.If you are an active McGill employee (ie: currently in an active contract or position at McGill University), do not apply through this Career Site. Login to your McGill Workday account and apply to this posting using the Find Jobs report (type Find Jobs in the search bar).Statistical Foundations of Data AnalyticsMGSC 401 001Mondays 8:35 - 11:25Start Date: January 5, 2027End Date: April 14, 2027CL Credits: 3Number of Class Hours: 39Remuneration: $11,824.00Deadline to apply: October 15 at 11:59 pmThe Desautels Faculty of Management is inviting applications to teach a course in Winter 2027. Please complete the online application form and upload required documents. Applications will be ranked according to the collective agreement between McGill University and the MCLIU. Preference will be given to the qualified applicant with the most priority points.Teaching Qualification Requirements:Education:PhD (or its equivalent), Master's, or Bachelor's degree in Business (with ample experience in data analytics courses and machine learning). Preferences will be given to those holding a degree in Operations Management, Industrial Engineering, or Operations Research.Experience:Candidate must be fluent in AI algorithms, R-studio, statistical learning, and must have a track record in teaching such topics. University teaching experience required.LocationARMST 075For any questions, please contact [e-mail] applying, please note that to work at McGill University, you must be both authorized to work in Canada and willing to work in the province of Quebec at the campus where the position is based / located.McGill University is an English-language university where most teaching and research activities are conducted in the English language, thereby requiring English communication both verbally and in writing.Hiring Unit:Desautels Faculty of Management -Operations Management AreaCourse Title:Statistical Foundations of Data AnalyticsSubject Code:MGSC 401 001Location:ARMST 075Schedule:Mondays 8:35 - 11:25Deadline to Apply:2026-10-15McGill 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, [e-mail].