Finding Crypto Exchange Hiring Signals: The Manual Approach
Before we built Signalmap, we tracked exchange hiring signals manually. Here is the methodology — and why we automated it.
The Manual Sources
LinkedIn: Search "[Exchange] jobs" with location and department filters. Refresh weekly. Track counts in a spreadsheet.
Greenhouse/Lever/Ashby: Most exchanges use one of these ATS platforms. Their job boards are publicly accessible and update daily.
Cryptojobslist / Web3.career: Aggregators that pull from exchange job boards. Useful for quick overviews but incomplete.
Reddit (r/cryptojobs, exchange subreddits): Exchanges occasionally post there; community members report layoffs/surges.
What Manual Tracking Misses
Manual tracking gives you snapshots. You miss: (1) trend direction (how fast is it growing?), (2) department composition (what are they specifically building?), (3) historical context (what did this pattern precede last time?).
Why Systematic Matters
Our dataset covers 10 exchanges × 18 months × daily tracking = 54,000+ data points. The pattern recognition that drives our 83% prediction accuracy requires that depth. A weekly LinkedIn check captures volume but misses the signal.