U.C. Berkeley Salaries

INSTRUCTOR SALARIES BY DEPARTMENT

by Jared Wilber · December 2017



Among all higher-education institutions in the world, U.C. Berkeley employs the highest number of Nobel Prize winners. You can seem them strolling about campus, there are parking spots reserved for them; even the director of the research lab I worked in throughout my undergrad earned the award in Physics. That said, the faculty talent doesn't end at Nobel Prize winners - with a top 10 worldwide ranking, Berkeley's faculty is amazing across the board.







While the subject may be taboo, I was always curious as to how much money the Professors made from their positions. After all, any number of them could have gone into industry and made a killing, so surely they must be well-compensated by the university. Luckily for us, this information is public domain. (Even luckier for us, Sahil Chinoy of the Daily Cal created an open-source database for the data).





Below, I've visualized the data using a tree map. Each rectangle is sized by its salary, relative to others in the same selection. Colors denote teaching level (e.g. Professor, Lecturer, etc.), and the distribution of teaching level can be viewed via the Display Teaching Level checkbox. The scroller allows for additional color subsetting by salary. Use the filter to select a major you'd like to investigate.





Filter by Department All Departments ───────── African American Studies Agricultural & Resource Economics Anthroplogy Architecture Art History Art Practice Astronomy Bioengineering Biology Business Chemical Engineering Chemistry City & Regional Planning Civil & Environmental Engineering Classics College Writing Comparative Literature Computer Science Demography Earth and Planetary Science Economics Education Electrical Engineering E.E.C.S. Energy & Resources Engineering English Environmental Design E.S.P.M. Ethnic Studies French Gender & Women's Studies Geography German History Ind. Engineering & Ops Research Information Interdisciplinary Studies International & Area Studies Journalism Landscape Architecture Law Linguistics Material Science & Engineering Mathematics Mechanical Engineering Middle Eastern Studies Music Near Eastern Studies Nuclear Engineering Nutritional science Optometry Philosophy Physics Political Science Psychology Public Health Public Policy Rhetoric Scandinavian Languages Slavic Languages and Literature Social Welfare Sociology South & Southeast Asian Studies Spanish and Portuguese Statistics Display Teaching Level



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Author: Jared Wilber





As expected, there is a direct relationship between teaching-level and salary: the higher one is in the hierarchy of instruction, the better off they are compensated. There is also some salary variance related to department; it appears departments that fit into the STEM umbrella see higher ceilings for salary than those that do not. This observation remains true across teaching-levels.

SALARIES BY DEPARTMENT





Students are often berated for the financial prospects of their major; is it the case that professors of these berated majors make less than their counterparts in other departments? In an effort to investigate any department-level difference in salary, we can compare faculty salaries at a more macro level, observing how aggregate salaries differ between departments.



To avoid skew from very high-paying professors (such as the Nobel Prize winners mentioned previously), we'll look at the median salaries of faculty by department.









As we saw in the treemap previously, department appears to be a driving factor for salary. In general, more STEM-focused departments see higher salaries. This may be for reasons of funding (Berkeley is a research institute and STEM departments often receive higher grants), demand, or location (Berkeley's proximity to Silicon Valley means high -compensation alternatives are nearby).





Data And Methodology





As mentioned previously, the data is publically accessible, and the Daily Cal's Sahil Chinoy created an open-source database using the data. Preparing the data for analysis required some light data munging, which was accomplished using R. The visualizations were created using Javascript's D3 library.







