A Machine Learning Model for Salary Estimation
Some time ago, I tried to scrape every Bay Area profile off LinkedIn until the site blocked my entire office network (Lesson learned: Use a proxy). This was Bad because we were (and still are!) hir…
A Machine Learning Model for Salary Estimation launched on January 8, 2016 with 83 votes, #652 of 4,523 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 10 years on.
In plain words
This machine learning model estimates salaries based on LinkedIn profile information, designed for recruiters and hiring teams in the Bay Area. It uses Latent Semantic Indexing to analyze profile data and maps job titles to salary predictions using GlassDoor salary information. The tool helps hiring managers quickly assess compensation ranges for candidates during recruitment.
written from the facts on this page · September 2026
From the sources
Some time ago, I tried to scrape every Bay Area profile off LinkedIn until the site blocked my entire office network (Lesson learned: Use a proxy) . This was Bad because we were (and still are!) hiring . The goal was to collect enough data to create a set of classifiers that could estimate a person’s salary from their LinkedIn profile. LinkedIn profiles were decomposed using Latent Semantic Indexing and mapped to salary estimates based on users’ current job titles. I scraped all the Bay Area salary information from GlassDoor . Now when we encounter a new profile, we can perform a similarity query, find the nearest matching profiles, and return their salaries. Previously this was all…from elaineou.com
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