Joining Data Course Staff

Apply to be an Academic Intern

We’re looking for students at UC Berkeley who are passionate about data science to be Academic Interns for Data 8 and Data 100 for Spring 2022! If you are interested and have taken Data 8 and/or Data 100 and received a B or better (or a P for all semesters in 2020, Spring 2021, or Summer 2021), please consider applying!

Serving as an Academic Intern is a great way to help current students achieve mastery and have a good experience in Data 8 and Data 100. It is also a great way to prepare for becoming a tutor or UGSI in the future!


All Academic Interns enroll in a mandatory 1-unit P/NP class offered by the course faculty. This corresponds to three to four hours of time commitment per week.

For Data 8, the typical weekly breakdown is:

  • 1 hour of preparation (e.g. studying the week’s assignments, consulting with senior staff, etc.)

  • 2 hours of assisting students

For Data 100, the typical weekly breakdown is:

  • 1-2 hour of preparation (e.g. studying the week’s assignments, consulting with senior staff, etc.)

  • 1 hour of assisting students

  • 1 hour for pedagogy practice, (U)GSI check-ins, AI team meetings, etc

APPLICATION DEADLINE: Friday, 1/21 at 11:59pm PDT

Data 8 Application:

Data 100 Application:

If you have any questions, feel free to send them to 

wendykimm@berkeley (for Data 8) and (for Data 100

Apply for an Academic Student Employee position

To apply for an Academic Student Employee position for a Data course, submit BOTH forms below:

  1. ASE Application (required)
  2. ASE Supplemental Application for Data Courses (required)

The priority deadline to apply for Spring 2022 was Friday, October 8, 2021.

Applications may be submitted after October 8, and will be reviewed as long as positions remain available.

Data Course Staff Overview

The Division of Computing, Data Science, and Society appoints graduate and undergraduate students to support its instructional programs. Our outstanding staff teams bear significant responsibility for our students’ experience and learning in Data classes. Staff team members also form strong bonds with each other, mentor junior members, and create staff networks for academic and professional development.

Course staff positions are Academic Intern (AI), Reader, Group Tutor, Undergraduate Student Instructor (UGSI), and Graduate Student Instructor (GSI). The last two titles are often jointly abbreviated as (U)GSI.

Academic Interns

Note: Academic Interns are not Academic Student Employees (ASEs).

Academic Internship is a common starting point for staff in Data 8 and Data 100. Academic Intern positions require enrollment in a P/NP class, typically for 1 unit. Correspondingly, the expected time commitment is 3 hours per week on average. AIs do not receive financial compensation. Typical responsibilities consist of providing support for students in discussion sections, labs, or office hours, supervised by (U)GSIs. The primary selection criteria are motivation for teaching and overall academic performance including performance in the class. 

All the other course staff positions are Academic Student Employee (ASE) positions for which there is financial compensation. The table below provides a brief description of the typical responsibilities as well as campus requirements and salary scales.

Please note:

  • Detailed responsibilities for each position depend on the course and its instructors.
  • The number of AI and ASE positions in a course can vary across semesters depending on the budget, course enrollment, and course structure.
  • Undergraduate applicants who have no prior teaching experience are encouraged to consider AI, Reader, or Group Tutor positions before applying to be UGSIs.

What positions are available?

Position Typical Responsibilities Courses Campus Requirements Salary
Reader Primarily responsible for grading and office hours. Data 102 Requirements for Readers Salary for Readers
Group Tutor Primarily responsible for academic support in office hours or small-group tutoring sessions; also some grading. Data 8, 100, 140 Requirements for Group Tutors Salary for Group Tutors
Undergraduate/Graduate Student Instructor

Teaches discussion and lab sections; collaborates on diverse aspects of course execution. 

GSIs are hired for 10 hours/week or more. Most UGSIs are hired for 8 hour/week positions. Some experienced UGSIs are for 20 hours/week.

Data 8, 100, 102, 140

Requirements for UGSIs

Requirements for GSIs

Salary for GSIs

Typical Timeline and Process

  • ASE applications for the Summer and Fall are released in March or April. ASE applications for the Spring are released in October. Selection starts after the priority deadline for submission, but applications remain open for several weeks after that.

  • The application for Academic Interns for Fall semester is released in June or July, and the application for Spring semester is released in January.

  • Selection for ASE positions is a collaborative effort by the Faculty Director of Pedagogy, the course instructors, and relevant DSUS staff. Selection of AIs is a collaboration between the Faculty Director of Pedagogy, the course instructors, and some senior course staff.
  • Offers are made starting shortly after the priority deadline. The process can continue till the start of the semester of appointment, for example due to changes in appointees’ own plans.

Some Common Pathways

Berkeley offers a uniquely innovative set of undergraduate Data Science courses. 

Applicants for Graduate Student Instructor (GSI) positions who have neither taken nor taught the course for which they are applying should describe the background that qualifies them for the position. Qualified graduate students have priority over undergraduates.

Teaching is a skill that develops over years of experience. All Data course staff participate in regular meetings to discuss pedagogy and best practices. Undergraduate staff typically start as AIs or Tutors and later apply for positions of greater responsibility. Here are some paths commonly taken by undergraduates on our staff teams.

  • Data 8 and Data 100: A common progression is AI, then Tutor, then UGSI, with at least one semester as each of AI and Tutor. 

  • Data 140: The typical progression is Tutor, then UGSI, with at least one semester as Tutor.