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A simple tool to help with job search via Google (and why) – Joseef

Hacker News

A simple tool to help with job search via Google (and why) – Joseef

TL;DR: Google has all the data and allows searching several companies job portals at once. That's how I've found my current position. This tool helps to manage queries. Some time ago it became apparent to me that most job boards I know became aggregators — most companies have their own job portals or at least pages on their sites, and those aggregators most of the time just collect postings. Of course they try to add value to it, but sometimes they try too much (adding complex interface), they choose what companies to show to you and postings become stale. So I tried searching on companies' job boards directly with Google excluding middleman, as those portals often don't have search features, and found my current position! At that time I stored queries in my notebook. But recently I've realized that Google is even more powerful — it allows searching on several portals at once. With this, complexity of queries starts to grow and managing queries in the notebook becomes difficult — queries are too long and hard to edit (add or exclude portals). Initially I thought that it was too simple to be shared with others (anyone can Google), but when complexity started to grow I made this page and it looks like now it may be useful to others. Hope it helps you!

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Product HuntOn track for Day 1 leaderboard · Strong signals: google · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
37%37% 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
14%14% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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