Quickly Filter Through Who's Hiring Posts

Hacker News

Hi all, I made this tool to sift through all the who's hiring posts. You'll need node / npm, but it works locally. It includes 2019 data. In the future, I hope to include all who's hiring posts with better graphs to visualize it. You can download it and play with it from here: https://github.com/vishaldpatel/jobstats And if you do, I'd love feedback! Including code feedback. There's some stuff that I haven't followed. Thank you! - V

Visit product View on Hacker NewsAug 2, 2019

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TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: including · Missing: https docs, excited, just released

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: visual, code · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: including · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

21%21% 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, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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