CUPE-Summer - TA MIAZ

Description

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.

Number of positions:

Expected Enrolment:

Work

Start Date:

Work End Date:

Total

Work Hours:

Hourly Rate:

The academic year starts on September 1 and ends on August 31.

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

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Language of Work:

Requirements and Nature of Work:

Must have strong theoretical knowledge of data science techniques such as regression, classification, clustering, survival analysis, time series analysis, association rule mining, and collaborative filtering. Hands-on experience with industry tools and programming languages, particularly Python and SQL, as well as knowledge of application deployment, is required. Should have excellent communication skills and the ability to simplify complex topics to support student comprehension.

Preference will be given to candidates who have completed a related course with a minimum grade of A, and/or who have previous experience as a teaching assistant for a related course, and/or worked on data science projects in an industry setting.

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.