SESSIONAL FACULTY - MMGMT 731, Industry-Partnered Project, …, Hamilton

Job ID 76294 Job Title SESSIONAL FACULTY - MMGMT 731, Industry-Partnered Project, 2026/2027 Multi-Term Regular/Temporary Temporary Location Ron Joyce Centre Open Date 2026/05/20 Job Type Limited Term (<12 months) Close Date 2026/06/02 Employee Group CUPE Sessional Faculty Favorite Job Department DSB Grad Programs Full/Part Time Part time Job Code 001095 Existing Vacancy Yes - Newly Created Position Contract Duration 7 Months Target Number of Openings 1 Hours per Week 14 Posting Details Number of Sections Available: 1 Number of Units per Section: 6 Location (on/off campus): RJC Projected Enrollment: 45 Projected TA Support: 45 C01 TBD subject to change Wage Rate*: The DeGroote School of Business offers a pay rate commensurate with qualifications and related teaching experience in a range from $18,871.46 to $19,500.00. The exact rate of pay is determined at the sole discretion of the employment supervisor, according to standard evaluation criteria. Required Qualifications: A Master's degree in a Business Administration Advanced analytics & AI Expertise: demonstrated expertise in data analytics, Big Data, and AI implementation 8+ years of relevant industry experience, working with real-world analytics applications across sectors Proven ability to communicate complex analytical concepts to diverse, particularly AI and data-driven decision making. Job Description The MMAIA Area within the DeGroote School of Business invites applications for the following teaching position to be offered in the 2026/2027 Academic Year. This course is a multi-term course that will be taught at the beginning of the Fall 2026 term to the end of the Winter 2027 term. Chair: Dr. Manish Verma Course Name/ Number: MMGMT 731, Industry-Partnered Project Course The Industry-Partnered Project will provide students with opportunities to explore, practice, and refine the key capacities that program leadership has identified as crucial for professionals in contemporary fields that utilize analytics. Students will develop mathematical and computer modeling abilities, insights on the selection of appropriate tools and algorithms, and the ability to process and analyze data in combination with the contextual expertise and the soft skills needed to formulate and communicate interpretations of data and outputs relevant to business and organizational decision-making. How To Apply 1. A cover letter stating your intent to apply for the position (including your address, phone number, and email address) and emphasizing your experience with the material to be taught. 2. A resume listing your academic qualifications and relevant employment experience. 3. For current or previous McMaster sessional faculty, information necessary to determine your current and aggregate seniority (as defined by Article 20 of the Unit 2 Collective Agreement). Questions may be directed to CUPE 3906 ( 4. Names and contact information of two references If you require this information in an alternate/accessible format, please contact Employee/Labour Relations at extension 26468. Employment Equity Statement McMaster University is located on the traditional territories of the Haudenosaunee and Mississauga Nations and within the lands protected by the “Dish With One Spoon” wampum agreement. The diversity of our workforce is at the core of our innovation and creativity and strengthens our research and teaching excellence. In keeping with its Statement on Building an Inclusive Community with a Shared Purpose, McMaster University strives to embody the values of respect, collaboration and diversity, and has a strong commitment to employment equity. The University seeks qualified candidates who share our commitment to equity and inclusion, who will contribute to the diversification of ideas and perspectives, and especially welcomes applications from indigenous (First Nations, Métis or Inuit) peoples, members of racialized communities, persons with disabilities, women, and persons who identify as 2SLGBTQ+. As part of McMaster’s commitment, all applicants are invited to complete a confidential Applicant Diversity Survey through the online application submission process. The Survey questionnaire requests voluntary self-identification in relation to equity-seeking groups that have historically faced and continue to face barriers in employment. Please refer to the Applicant Diversity Survey - Statement of Collection for additional information. Job applicants requiring accommodation to participate in the hiring process should contact: - Human Resources Service Centre at 905-525-9140 ext. 222-HR (22247), or - Faculty of Health Sciences HR Office at ext. 22207, or - School of Graduate Studies at ext. 23679 to communicate accommodation needs. Hybrid Work Language To ensure an ongoing and vibrant University community that meets the needs of our students, staff and faculty and supports the University mission, ability to work on-site continues to be a requirement for most University positions. The University is supportive of exploring flexible work arrangements that effectively balance operational needs and employee interests. Interview Experience At McMaster University, we believe in a comprehensive and inclusive interview process. Our interview methods encompass a variety of approaches that allow our hiring teams to provide a flexible and accessible experience for engaging with our candidates. Throughout your recruitment process at McMaster, you may be requested to participate in a variety of formats, that may include in-person, virtual or recorded interviews. If you have any questions as you move through the hiring process, please reach out to or the HR contact associated with your position of interest. AI Statement McMaster and its third-party partners may use AI tools to screen, assess, or select applicants during the hiring process. Please note that currently our recruitment platform does not use AI nor is it part of our current recommended recruitment process. Apply on Kit Job: kitjob.ca/job/2o45hy