We

We are going to help you land a job from today's Who is hiring thread

Hacker News

We are going to help you land a job from today's Who is hiring thread

Hi HN! We are Pascal and Beroli, co-founders of Voorjob (https://www.voorjob.com) a small startup from Copenhagen that is going to help you get a new job from today's Who is hiring thread. We started sketching this idea while I was looking for a new job opportunity at October's thread. During the job search I went thought a process that might be familiar to many of you: sending dozens of resumes, writing custom cover letters, having interviews, getting ghosted, the whole nine... That was when we realized one thing: Today's hiring process with all those fancy ATS, resume parsers and ML algorithms, is kind of broken, the power is almost entirely with the side that is hiring. We decided to fight back! At first we are trying to solve the data manageability of job hunting, our initial set of features encompasses a few tools that will help you thought this journey: backlog of applications, application manager, assets (resumes and cover letters) In addition to the management/tracking features, you get insights! Find out which cover letter (or resume) is working better, you can track variations for different positions, learn your bounce rate, your conversion rate and get to know where to focus your efforts. And that is just the beginning, we have a backlog with 100's of new features and improvements, and we hope to prioritize and grow it from your feedback. One of our early users, agreed to share his job stats with the HN community so you can peek a look at what kind of information our product provides: https://www.voorjob.com/app/link/6da0ba76-e753-4012-95fd-53409e6ab78c/ Since everyone here has probably hunted for jobs before, we would love to listen your feedback and learn more about the pain points that you think we should be focusing next. Happy hunting! [1] https://news.ycombinator.com/item?id=21612151 [2] https://news.ycombinator.com/item?id=13783786 [3] https://news.ycombinator.com/item?id=14729005

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92%92% predicted probability of success on Indie Hackers, 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: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host, users · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, using · Missing: mac, agents, macos
21%21% 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, revenue
12%12% 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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