A system that continuously tracks job postings across companies, logging posting dates and measuring duration, to identify 'ghost jobs' and broader hiring patterns.

Last year I was looking for a new role. I sent out applications, did the prep, waited. What came back was mostly nothing. Not rejection emails, just silence. The job listings I'd applied to stayed live for weeks. Some for months.As a software engineer, I decided to dig into it properly. I built a system to continuously track job postings across companies, logging posting dates and measuring how long roles stay open before closing or don't. After 35,000+ listings across 200+ companies, some patterns are hard to ignore. Some listings have been open for 700+ days at companies you'd recognize. Others post 90% of their open roles within a single month, a signal that's harder to fake than a press release.I published two initial insight pages based on this work:
- Which companies are posting most aggressively right now
- Job listings that have been open for over a yearWhat I didn't expect is that the same signals useful for detecting ghost jobs also say something broader about a company's hiring momentum, recruiting intensity, pipeline health, where talent bottlenecks might exist. I'm not sure yet where this leads, but I'll keep expanding the dataset and publishing more insights as I go.Would genuinely love feedback on the methodology, interpretation, or obvious blind spots in the data.