How to Build a Talent Intelligence Platform with Job Data Scraping

Talent intelligence — understanding who is hiring, for what roles, at what salaries — is a billion-dollar industry. Companies like LinkedIn Talent Insights charge thousands per seat. But the raw data is publicly available on job boards. Here's how to build your own talent intelligence platform by scraping job postings and analyzing hiring trends. The Business Case Talent intelligence answers questions like: Which companies are scaling their AI teams? What's the real salary range for senior engineers in Austin? Which skills are trending up vs. declining? How long do positions stay open (time-to-fill)? Recruiters, HR teams, and investors all pay for these insights. Setting Up pip install requests beautifulsoup4 pandas scikit-learn Scraping Job Listings We'll target publicly accessible job boards. Use ScraperAPI for proxy rotation: import requests from bs4 import BeautifulSoup import pandas as pd import re from datetime import datetime import time SCRAPER_API = " https://api.scraperapi.co