Building a Job Salary Intelligence Tool with Python

Building a Job Salary Intelligence Tool with Python Salary transparency is increasing, but data is scattered across dozens of platforms. In this tutorial, we will build a Python tool that aggregates salary data from multiple sources to give you real intelligence for negotiations, hiring, or market research. Architecture Overview Our tool will: Scrape salary data from public job postings Normalize titles and compensation ranges Store everything in a structured format Generate reports with percentiles and trends Setup pip install requests pandas matplotlib Scraping Job Postings with Salary Data Many job boards now require salary ranges. Let us start by extracting them: import requests import re import pandas as pd def extract_salary_range ( text ): patterns = [ r " \$([\d,]+)\s*[-to]+\s*\$([\d,]+) " , r " ([\d,]+)k\s*[-to]+\s*([\d,]+)k " , ] for pattern in patterns : match = re . search ( pattern , text , re . IGNORECASE ) if match : low = float ( match . group ( 1 ). replace ( " , " , "