Sessional Faculty in Data Science

3 days ago

Toronto, Ontario, Canada University of Niagara Falls Canada Full time $7,200
Teaching Position in Predictive Analytics
The University of Niagara Falls Canada invites applications for a teaching position in predictive analytics. We are seeking a highly qualified individual to teach graduate-level courses in this area and contribute to the growth of our Master of Data Analytics program.

Job Description:
The successful candidate will have a Doctorate/Ph.D. in Data Science, Computer Science, Statistics, Math, Economics, or a related field, with a focus on predictive analytics or data analytics. They must also have teaching experience in predictive analytics, regression modeling, data mining, and machine learning at the undergraduate or graduate level. Strong familiarity with software and programming languages used in predictive analytics, including SAS and Excel, is required. Industry experience in the application of predictive analytics in domains such as healthcare, consumer behavior analysis, credit risk assessment, etc., is a significant asset. The ability to mentor and advise students in both academic and professional development contexts is also essential.

Responsibilities:
This faculty member will be responsible for delivering lectures, preparing course materials, assessing student work, and providing feedback. They will also collaborate on curriculum development to ensure course content aligns with industry standards and trends. The successful candidate will be expected to integrate tools like SAS and Excel into their teaching and use internal software to manage grades and track progress. They will also contribute to departmental initiatives and participate in ongoing professional development.

Key Qualifications:
A Ph.D. in Data Science or a related field, with a focus on predictive analytics or data analytics; Teaching experience in predictive analytics, regression modeling, data mining, and machine learning at the undergraduate or graduate level; Familiarity with software and programming languages used in predictive analytics, including SAS and Excel; Industry experience in the application of predictive analytics in domains such as healthcare, consumer behavior analysis, credit risk assessment, etc.

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