Information Systems - 315 (Adjunct Faculty)

at  Brigham Young University

Job Classification: Adjunct Faculty-Teaching
Posting close date: June 25, 2024
Start date of this position: September 4, 2024
Required Degree: Master’s Degree in Information Systems, Business Administration, Statistics, Mathematics with an applied focus, or related field. The required degree must be completed by the start date.

Experience: Ability to teach the following subjects at a beginner level:

• Python programming in Jupyter Notebooks
• Environments: Google Colab and/or VS Code
• Topics including Python packages:
• First half of the class:
• Python variables, flow control, input-processing-output, collections, iterations, packages, Pandas DataFrames, reading/writing from CSVs, JSON, SQL databases, debugging, functions, automation
• Second half of the class:
• Univariate statistics and visualizations (using Matplotlib and Seaborn)
• Bivariate statistics and visualizations (scipy, numpy, pandas, plotly)
• Data cleaning in Pandas DataFrames

Although teaching experience is not required, it is preferred.

Duties/Expectations: This position is to teach IS 315: Introduction to Python Data Analytics. Course content and teaching materials will be provided. Teaching assistants will be hired to assist with the course as well.

• Teach course M/W 11 am - 12:15 pm from September 4, 2024 - December 11, 2024 (Final grades due December 27, 2024)The candidate should be a current professional in the field of data science or have significant recent experience.
• The curriculum, book, and assessment materials have already been created uniquely for this new course.
• It is expected that the candidate will commit to teaching for the full term or semester.
• The candidate is welcome to invite network connections to be guest speakers or otherwise share their personal, unique knowledge from their professional experiences.
• Pay will be dependent on instructor experience, course credit hours, and student enrollment.

Must reside in the state of Utah to be eligible for employment consideration. Must be willing to teach the course(s) in person, on campus.
Information required at the time of application: Please list the individual contact information for each of your three recommenders on the faculty application. At some point during the selection process, they may be contacted to submit their letters of reference electronically.
Document(s) required at the time of application: Please attach your updated Curriculum Vitae and cover letter to the faculty application.

• Teach course M/W 11 am - 12:15 pm from September 4, 2024 - December 11, 2024 (Final grades due December 27, 2024)The candidate should be a current professional in the field of data science or have significant recent experience.
• The curriculum, book, and assessment materials have already been created uniquely for this new course.
• It is expected that the candidate will commit to teaching for the full term or semester.
• The candidate is welcome to invite network connections to be guest speakers or otherwise share their personal, unique knowledge from their professional experiences.
• Pay will be dependent on instructor experience, course credit hours, and student enrollment