Assistant Professor - Data Analytics (Academic Year Tenure Track)
Big Rapids, MIFull-time$100–105K/yrSeen todaySeen in employer's feed today
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Job overview
Ferris State University’s Marketing Department seeks a diverse group of outstanding applicants for a full-time, tenure-track Data Analytics position. The successful candidate will teach undergraduate and graduate courses in Data Science and Analytics and should be able to teach a range of required courses across the department’s bachelor’s and master’s programs. The posting lists subjects including statistics, calculus, Python, machine learning, and data mining.
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Full job description
Position Title: Assistant Professor - Data Analytics (Academic Year 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 benefits 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: Academic Year (faculty) At Will/Just Cause: Just Cause Summary of Position: The Marketing Department in the College of Business at Ferris State University seeks a diverse group of outstanding applicants for a full-time, tenure-track position in Data Analytics. We are seeking a qualified individual to teach a selection of undergraduate and graduate courses in Data Science & Analytics. The applicant should be able to teach a range of the required courses in the Business Data Analytics BS, Data Science and Analytics BS, and MS in Data Science & Analytics programs. The subjects taught are Introduction to Statistics, Inferential Statistics, Applied Linear Models, Applied Statistical Methods, Calculus, Python, Machine Learning, Visual Data Analytics, and Data Mining Tools, including association rules, clustering, predictive analytics, text & web mining, and data warehousing and intelligence. The applicant should possess knowledge of most of the following software: ⢠Excel â" Statistical functions & pivot table ⢠IBM-SPSS Modeler, SAS Enterprise Miner, and/or
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