Sessional Lecturer - MMF2030H1F: Machine Learning (Section LEC 0101)
About The Position
The course will cover machine learning from both a theoretical and practical point of view, with a focus on pragmatic applications & real industry examples. Topics will cover supervised & unsupervised learning, as well as high level workflows from business problem definition down to analysis and integration with business strategy. Students will be encouraged to understand problems from a quantitative point of view, as well as through the lens of strategy and business usage. The course will cover theory, applications & common usage of key machine learning techniques, as well as case studies from the financial and professional services industries. The course evaluation will be based on participation and a group project, where students will be encouraged to apply a range of techniques covered to a business problem.
Requirements
- Advanced degree in Mathematical Finance
- Industry experience in supervised and unsupervised learning modern applications of machine learning
- Prior experience teaching this course (or a similar course) at the university level
- Ability and experience teaching large classes
Nice To Haves
- Industry experience in integration with business strategy
Responsibilities
- Preparation and delivery of lectures in this course
- Preparation, supervision and grading of tests and examinations in accordance with university regulations
- Providing scheduled office hours for academic counseling of students
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What This Job Offers
Career Level
Mid Level
