Lecturer - Department of Economics (Part-Time) - Military veterans preferred

The John E. Walker Department of Economics invites applications for a part-time instructor to teach more advanced techniques associated with analyzing large data sets frequently used in economic analysis. In this course, the topics include data collection and web scraping techniques, data organization, supervised segmentation, support vector machines, and linear discriminant analysis. The course emphasizes using and implementing modern data analysis to examine and analyze data sets frequently encountered in business and economics.

In the spring, the instructor will teach a class that looks at some modern machine-learning techniques. Included in these advanced topics are ridge regressions, shrinkage methods, lasso regressions, principal components, partial least squares, polynomial regressions, and tree-based methods, including random forests. The ideal candidate should be comfortable with these topics.

The qualified candidate should have a Masters Degree in Economics, Data Science, or a related field. Experience with GIS would be useful.

Please provide a cover letter, C.V., and the names and contact information for three references via Interfolio:

http://apply.interfolio.com/146268

Applications received by June 5, 2024 will receive full consideration and the position will remain open until filled.