The Research Computing Education initiative (RCE) in partnership with the University Library System (ULS) and the Health Sciences Library System (HSLS) are looking for teaching assistants (TAs) to support informal data science education at the University. In particular, we are looking for students familiar with the Python programming language, data visualization, databases, and fundamental principles and techniques of data cleaning and data management.

This position would primarily support the development and delivery of instructional materials for introductory data science workshops for students, faculty, and staff. In addition, this position would support and help create an informal learning community centered around data science.

The TA will be responsible for:

  • Instructional Support – Assisting with and running sections of the Data Basics workshops either in-person or online, synchronous or asynchronous.
  • Community Support – Supporting the participants during live sessions and asynchronously via an online community platform such as Slack.
  • Content Development – Helping develop or redesign instructional content to support multiple modes of instruction (online/in-person, synchronous/asynchronous).
  • Evaluation & Assessment – Helping faculty to develop and evaluate teaching and instructional materials through surveys.

Preferred Qualifications:

  • Basics of the Unix/Linux command line, Git, GitHub
  • Python programming environments, including Jupyter Notebooks
  • Python programming language
  • Python libraries, including pandas and matplotlib
  • Reading data from multiple text file formats, including CSV & JSON
  • Basic data visualization
  • Basic relational database management and SQL

As you review the qualifications, please think about how your qualifications are transferable if (at first) they do not seem directly related. We encourage you to apply, even if you don’t believe that every one of our preferred qualifications described is met.

Click here for more information and to apply.


(Photo by Seema Miah on Unsplash)