I
I analyzed 3,465 remote job listings – 72% hide salary information
Hacker NewsI analyzed 3,465 remote job listings – 72% hide salary information
I collected and analyzed 3,465 remote job listings to find trends in pay transparency, job titles, and industries. The full write-up includes charts and takeaways (spoiler: 72% of jobs don’t show salary). I’d love feedback on the methodology or suggestions for other data points to explore next.
Share cardActual performance
1points
1comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos18%18% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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