CUPE-Hiver/Winter 2027- TA-CSI4142A

Posting Reason:

New Position

Location where work is to be performed:

Main Campus

Session:

2027 Winter Semester | Trimestre d'hiver

Faculty:

Faculté de génie / Faculty of Engineering

Unit:

EECS_ST

Job Classification:

Teaching Assistant/Demonstrator/Lab Monitor (CUPE)

Posting Type:

Cours précis / Specific course

Course Title:

Introduction to Data Science

Course Code:

CSI4142

Section:

A

Supervisor name (if known):

Date Posted (YYYY/MM/DD):

2026/10/22

Applications must be received BEFORE (YYYY/MM/DD):

2026/11/05

Description of tasks (hours):

Unless specified below, specific allocation of hours to various tasks should be articulated in a description of work negotiated and signed by you and the supervising professor prior to the commencement of work.

Recherche / Research:0

Préparation / Preparation:0

Contact avec étudiants / Contact with Students:0

Correction - Notation / Grading:0

Surveillance / Proctoring:0

Formation / Training:0

Autre / Other:0

Number of positions:

2

Expected Enrolment:

42

Work Start Date:

January 01, 2027

Work End Date:

April 30, 2027

Total Work Hours:

130

Hourly Rate:

AE-RA-Tuteur / TA-RA-Tutor : $33.83 ou/or $53.31 (Sept. 2026 - Aug. 2027)

Undergraduate students will be paid at the lower rate; while graduate students will be paid at the higher rate.

These rates do not include vacation pay nor statutory pay.

Method of Delivery:

IN PERSON

Language of Work:

Anglais | English

Requirements and Nature of Work:

Nature of Work:

Correcting assignments and lab reports, supervising labs, directing group projects, providing office hours, assisting in preparing labs, project descriptions and sample programs.  Correcting midterm. Proctoring.

Minimum Requirements:

Preference will be given to candidates who have completed this course or its equivalent and its prerequisite(s) with a mark of A or better.  Attend a TA workshop if necessary.  Must be ready for an interview if considered for this position. Excellent knowledge of data warehousing and data mining, including dimensional modelling, data staging, OLAP and SQL, data preprocessing, data mining techniques and machine learning frameworks.

Please note that the teaching method will be delivered: in person.

​NOTE: le nombre de postes et le nombre d'heures offertes sont tous deux assujettis aux inscriptions finales dans ce cours. Please note that the number of hours and positions offered may vary due to enrolments in that course.

Additional Information and/or Comments:

All University of Ottawa employees are required under provincial law to successfully complete all mandatory legislated training offered by the University. The list of training requirements may be modified by provincial law. If you are invited to continue the selection process, please notify us of any particular adaptive measures you might require. We may consult with the Health and Wellness sector of Human Resources, if needed. Any information you send us will be handled respectfully and in complete confidence.

The hiring process will be governed by the current CUPE 2626 collective agreement; you can click here to find out more.

The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact the academic unit to communicate the accommodation need.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.