| Position Title: | Assistant Professor - Data Analytics (9-month, Tenure Track) | |
| Location: | Big Rapids (Main Campus) | |
| Department: | 34500 - Marketing | |
| Advertised Salary: | $100,000 - $105,000; Salary commensurate with education, experiences and other requirements. | |
Benefits:
| Comprehensive benefit package (health care, vacation, etc.). Please see the following link for a list of benefits offered with this position. Faculty Health Benefit Plans | |
| FLSA: | Exempt | |
| Temporary/Continuing: | Continuing | |
| Part-Time/Full-Time: | Full-Time | |
| Union Group: | Ferris Faculty Association (MEA-NEA) | |
| Term of Position: | 9 Month | |
| At Will/Just Cause: | Just Cause | |
| Summary of Position: | The Marketing Department is seeking a qualified individual to teach a selection of undergraduate and graduate courses in Data Science & Analytics. The applicant should be able to teach an array of the required courses in the Business Data Analytics BS and the MS in Data Science & Analytics programs. Subjects include: Introduction to statistics, inferential statistics, applied linear models, applied statistical methods, calculus, programming, machine learning, visual data analytics, and data mining tools that include association rules, clustering, predictive analytics, text & web mining, and data warehousing and intelligence. Courses are to be taught in person on one of Ferris State University's Campuses or approved FSU sites. The candidate(s) selected for the position must reside in Michigan after acceptance of employment. The anticipated start date of this position is August of 2026 at the earliest and January of 2027 at the latest. | |
| Position Type: | Faculty - Temporary & Continuing | |
| Required Education: | Ph.D. or Ph.D. candidate graduating prior to January 1, 2027 with a Ph.D. in statistics, applied statistics, data mining, data analytics, business data analytics, data science, or a closely related field. | |
| Required Work Experience: | Experience in teaching statistics, data mining, data analytics, data science, machine learning, artificial intelligence, or a related field in face-to-face, mixed delivery, or online environments at a college/university level.
Industry, consulting, or research experience in statistics, data mining, data analytics, data science, and/or big data.
Demonstrated research and publication background. | |
| Required Licenses and Certifications: | | |
| Physical Demands: | - Office Environment
- Standing
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| Additional Education/Experiences to be Considered: | In-field industry with leadership involvement or equivalent teaching experience with consulting or research involvement in statistics, data mining, data analytics, data science, machine learning, artificial intelligence, big data, or a closely related field. | |
| Essential Duties/Responsibilities: | • Teach full-time during the 9-month academic year.
• Teach a selection of undergraduate and graduate courses in Data Science & Analytics. The candidate should be able to teach an array of the required courses in the Business Data Analytics BS and the MS in Data Science & Analytics programs. The subjects to be taught are Introduction to statistics, inferential statistics, applied linear models, applied statistical methods, calculus, programming, machine learning, visual data analytics, and data mining tools that include association rules, clustering, predictive analytics, text & web mining, and data warehousing and intelligence.
• Candidates should possess the ability to develop and deliver curricula activities for hands-on experiential learning integrated across multiple platforms (online, mixed delivery, and face-to-face).
• Candidate should be able to work independently and collaboratively with effective communication skills, both written and orally. The candidate is encouraged to serve as an advisor for our students in the Data Analytics Association at Ferris.
• Recruitment of students (including Dawg Days, Admitted Student Days, visits to high schools or career tech centers, and other University-outreach events) will occur throughout the academic year and include some Saturdays.
• Faculty is expected to engage in assessment of student learning and scholarly/professional development activities to enhance their teaching ability or learn new materials/techniques/so
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