Data scraping for salary benchmarking

Description

This project will develop a data scraper to collect salary records from a website that provides compensation data for faculty at public universities. When provided a list of faculty names and institutional affiliations, this program will search for the associated records, extract the relevant results, and copy the data into a spreadsheet. The purpose of this project is to explore the feasibility of automating an otherwise time-consuming data collection task required for benchmarking of faculty salaries in relation to peer institutions. This will ultimately facilitate a number of important tasks, including analysis of potential salary disparities within certain disciplines and faculty tracks.

Awards

• Highlighted Project

Students

• Matthew Lim

• Minh Nguyen

• Sindhu Ravi

• Vihang Mangalvedhekar

• Kevin Tsang

Advisors

• Fred Morstatter

• Ginger Clark

• T.J. McCarthy

Skills Required by the team

• Web Scraping

Final presentation resources

• Final presentation