Data • ottawa on
Professeur à temps-partiel régulier / Regular Part-Time Professor.The academic year starts on September 1 and ends on August 31.These rates do not included vacation pay nor statutory pay.These rate... Show more
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Description
:Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time ProfessorDate Posted (YYYY/MM/DD):
2026/06/05Applications must be received BEFORE (YYYY/MM/DD):
2026/07/06Expected Enrolment:
30Approval date:
2026/06/05Number of credits:
3Work Hours:
39Hourly Rate:
Enseignement / Teaching: $239.47 (2024-2025)The academic year starts on September 1 and ends on August 31.
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.
Course type:
BPosting type:
Régulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
ActiveCourse Schedule:
Jeudi | Thursday 19:00-22:00 - -Requirements:
Requirements
• Ph.D. in DTI, Data Science, Computer Science, Statistics, Mathematics, or a closely related field with a strong focus on Data Science, analytics, or AI/ML.
• Strong expertise in Data Science, including statistical modelling, machine learning, data visualization, descriptive and predictive analytics, and time series analysis, with applied experience in data engineering, data warehousing, big data analytics, and data workflows/pipelines.
• Demonstrated industry experience applying Data Science techniques to real-world problems, including the development and deployment of data-driven solutions in practical or production environments.
• Teaching experience in Data Science or related fields at the undergraduate and/or graduate level, with the ability to explain complex technical concepts to diverse student cohorts.
• Hands-on experience with modern Data Science tools and technologies, including Python, SQL, Spark, ML frameworks, and cloud platforms such as AWS, Azure, or Google Cloud, as well as familiarity with distributed data storage and processing systems.
• Proven data Science industry experience and demonstrated experience incorporating project-based or experiential learning approaches in teaching.
Additional Information and/or Comments:
The course is onlineAn acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience.
