Loras College
  • Business Analytics
  • Dubuque, IA, USA
  • To be discussed at interview
  • Part Time

Loras College is an equal opportunity employer committed to creating an educational and work environment that is inclusive, rich in diversity, and supportive of all students, faculty and staff. Individuals from diverse racial, ethnic, and cultural backgrounds, women, veterans, and persons with disabilities are strongly encouraged to apply.  Please visit www.loras.edu for additional information about Loras College.          

Loras College invites applications for an adjunct faculty position to teach graduate analytics courses such as Programming for Analytic Methods, Database Programming & Management and/or Marketing Analytics during the Spring 2021 semester.  The following are the relevant course descriptions:  Courses are held online one evening per week (except MAA 521, which is 2 evenings per week for 4 weeks) over a 7-week period with an in-person weekend held on the Loras Campus.

MAA-521: Database Programming (January Term) This course explores the fundamental concepts of relational databases: how they are designed, accessed, protected, and managed.  The primary focus is on database programming statements that retrieve, modify, summarize, analyze, and extract data. Storing of queries within the database for repeated use will be covered. 3 credits.

MAA-530 Programming for Analytic Methods (Spring) Business Analytics is the process of transforming data into business value. The Data Science course explores a variety of analytical methods for building models (predictive or explanatory). This course will focus on programming languages used for accessing, analyzing, and implementing such models. While many software platforms are available to automate various parts of this process, programming languages are commonly used primarily R and Python at present. This course exposes students to the use of these languages, focusing on their use for accessing and cleaning data sources and implementing models in a production environment. The subsequent course (Big Data Ecosystem) utilizes these languages for an understanding of the entire process of Business Analytics. While some students may develop a proficiency with coding in these programming languages, the purpose of the course is to provide sufficient exposure to the use of these languages for making business decisions regarding choices of software, human resources, and organizational structures necessary for developing Business Analytics efforts. 3 credits

MAA-560 Marketing Analytics (Spring) Marketing remains a branch of business as well as a social science, and is often characterized by the "4 Ps" of product, place, promotion, and price, and has been extended in many contexts to include people, packaging, and positioning. Each of these Ps is a candidate for improvement through the use of analytics. In Marketing Analytics, we consider the analytics of: (1) Pricing, Forecasting Sales, (2) Understanding customer demand, (3) Customer Value, (4) Market Segmentation, (5) Retailing, (6) Advertising, (7) Market Research Tools and (8) Internet & Social Marketing. Topics may include, but are not limited to, Price Bundling, Willingness to Pay, Profile Conjoint Analysis, Discrete Choice Analysis, Value Templates, Clustering and Collaborative Filtering, Bass Diffusion Models, Market Basket Analysis, Pay-per-Click Advertising, Principal Components Analysis, Measuring Nodes and Links, Network Contagion, and Viral Marketing Models. 3 credits.

A doctoral degree in Analytics or related field is preferred; a master's degree will be considered if the candidate has significant industry experience in analytics. Demonstrated excellence in teaching is preferred. 

Review of applications begins immediately and continues until the position is filled.  For more information contact James Padilla, Dean Noonan School of Business, Search Committee Chair, james.padilla@loras.edu, 563-588-7405.

To apply, please go to: https://loras.applicantpool.com/jobs/ to upload your letter of application, unofficial transcripts from advanced degree(s) awarded, curriculum vitae, as well as contact information for three professional references.  The finalist will need to pass a background check before receiving a written employment offer.

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