Statistics Teaching Jobs (NOW HIRING)

Reporting to the Chair, Department of Mathematics and Statistics, the incumbent oversees the day-to-day pedagogical, technical, and administrative operations of the Statistics Teaching Laboratory. The incumbent supports the delivery of laboratory-based and computing-based components of statistics courses by coordinating teaching materials, assisting with student support, supervising teaching assistants, and helping ensure consistency and quality across supported courses. The position also teaches a maximum of two threecredit courses per year, contributes to the development, maintenance, and continuous improvement of instructional materials, coding activities, datasets, and assessment tools, and serves as a resource person for students and instructors in statistical computing, data analysis, and laboratory pedagogy.

In this role, your responsibilities will include:

• Statistics Lab Operations and Coordination: Manages the daily operations of the Statistics Lab in support of the Department's teaching activities. Assists with scheduling, planning, and coordination of laboratory sessions and other Statistics Lab-supported activities. Monitors the impact of course enrolment on staffing, space, software, and other instructional resource needs. Maintains shared pedagogical and technical resources used in supported courses.

• Teaching Material Development: Develops, updates, organizes, and maintains laboratory manuals, assignments, practice materials, datasets, coding templates, guided examples, and other didactic resources for supported courses. Helps ensure that teaching materials remain clear, current, reusable, and aligned with course objectives. Contributes to the standardization and continuous improvement of Statistics Lab materials across courses and semesters.

• Statistical Computing and Technical Support: Provides expertise in statistical computing and data analysis in support of undergraduate teaching laboratories. Assists with the preparation, testing, validation, and refinement of scripts, notebooks, datasets, and other computational materials used in courses. Helps troubleshoot technical issues related to software, coding environments, packages, file formats, and reproducibility.

• Student Support and Instruction: Acts as a sessional lecturer and organizes, prepares, and presents lecture material for a maximum of two 3-credit courses. Supports students during laboratory sessions and through office hours by answering questions related to course material, data analysis, statistical computing, interpretation of results, and report preparation. Demonstrates analytical and computational procedures used in supported courses. Helps students develop sound practices in coding, documentation, data analysis, and communication of statistical results.

• Course and Curriculum Support: Collaborates with professors to ensure that laboratory activities are consistent with lecture material and course objectives. Contributes to the progression and continuity of analytical, computational, and communication skills across courses supported by the Statistics Lab. Identifies opportunities to improve the student learning experience and to strengthen the integration of theory and practice.

• Student Evaluation Support: Contributes to the preparation and maintenance of laboratory assignments, quizzes, tests, and examinations, in consultation with course instructors. Helps establish clear grading practices and supports consistency in the correction of laboratory-based evaluations. Assists in compiling laboratory grades and communicating evaluation-related information, as required.

• Supervision of Teaching Assistants: Assigns, trains, supervises, and supports teaching assistants involved in Statistics Lab-supported courses. Provides guidance on teaching expectations, course tools, grading practices, and appropriate student support. Helps ensure consistency in the delivery of laboratory sessions and in the interpretation of grading criteria across different sections and teaching assistants.

• Innovation in Teaching and Learning: Researches and evaluates new pedagogical, computational, and instructional tools relevant to statistics teaching. Helps adapt laboratory activities and student support practices to evolving learning environments, including the growing use of AI-assisted coding tools by students. Contributes to approaches that emphasize understanding, reproducibility, interpretation, debugging, and methodological reasoning.

• Academic Integrity and Good Practice: Supports the development of clear practices regarding coding, collaboration, reproducibility, and the appropriate use of AI tools in supported courses. Promotes sound documentation, transparent analytical workflows, and responsible use of statistical software and data resources.

What you will bring:

• Graduate degree (PhD Preferred) in Statistics, Biostatistics, Data Science, or a closely related quantitative discipline.

• 5 years' experience teaching in a post-secondary environment with strong experience in laboratory instruction, academic support, or the coordination of instructional activities in statistics or related areas.

• Strong knowledge of statistical computing and data analysis.

• Strong knowledge of R and/or Python, SAS, and of statistical computing workflows used in teaching.

• Ability to learn and adapt to new statistical, data analysis, and programming tools as needed to support evolving teaching needs and curriculum development.

• Ability to develop and maintain clear, pedagogically effective teaching materials.

• Ability to support students in coding, data analysis, interpretation, and written communication of results.

• Strong organizational, administrative, and time-management skills.

• Excellent problem-solving skills and sound judgment.

• Strong interpersonal and communication skills.

• Ability to work independently and collaboratively with faculty, staff, and teaching assistants.

• Commitment to service excellence and student success.

• Experience with LaTeX, R Markdown, Quarto, Jupyter, or similar tools for preparing reusable teaching materials.

• Experience with reproducible reporting and versioned teaching resources.

• Familiarity with current issues related to AI use in programming and higher education.

• Ability to work on a schedule with variable hours to meet operational needs.

• Bilingualism in French and English, oral and written.

#LI-GC1