HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
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Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#2I guess at least HR doesn’t have to read 1,000 resumes. Heck, to be frank, could they make sense of the first 10 resumes?
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#3Disregarding the fact that this thing is completely broken, its grading rubric is ridiculous to begin with (as was mentioned in the article itself, but I must reiterate how completely stupid this is):
> 35 points for open source contributions
> 30 for personal projects
I don't contribute to open source or have personal projects because I don't spend my free time doing what I do 40 hours a week to make a living. My 15 years of work experience is worth a maximum of 25%, so any company using this idiotic system would pass on me immediately. Open source and personal projects are fine, but in no sane world are they worth 65% of a resume's score.
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#4> I fail 65% of the time. Same exact resume, different luck.
As someone who’s run hiring pipelines for technical roles in the past few years, that’s actually a fantastic number. I objectively hate saying that, but it’s true.
35% chance of elevating a technical individual to the next stage with no effort? I’ve seen as many as 100+ applicants an hour even when including a domain specific screener question. That’s 35 “screened” applicants in an hour. Were valid candidates screened out? Yes. Does you still have a candidate pool 35x larger than you need? Unfortunately, also yes.
The volume of applicants is SO HIGH such that your chances of getting moved to the next stage are actually markedly worse if AI isn’t involved. If you didn’t apply immediately (using an AI bot) there’s 50+ people ahead of you, and an exhausted technical leader if they ever make it to your resume.
Referral bonuses exist for a reason.
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#5> I fail 65% of the time. Same exact resume, different luck. As someone who’s run hiring pipelines for technical roles in the past few years, that’s actually a fantastic number. I objectively hate saying that, but it’s true. 35% chance of elevating a technical individual to the next stage with no effort? I’ve seen as many as 100+ applicants an hour even when including a domain specific screener question. That’s 35 “s…
Is it? Or is it a 65% chance of a resume getting ignored before a single human sees it, reducing your pipeline's likelihood of catching qualified candidates by the same?
Gates that reduce resume flow-through are only useful if their reduction is correlated with quality. Otherwise they're just dragging out your hiring process or unnecessarily causing you to ultimately lower your hiring bars.
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#6An alarming number of people don't understand that LLMs work via purely stochastic processes, so I'm happy to see in-depth pieces like this. I'm looking for a job and maybe this is why it's so hard to get a callback these days: resumes are just dumped in some LLM black hole and no one really knows how it works. The author says:
> temperature 0.1 — low, supposedly nudging the model toward deterministic outputs
This is not correct (and is briefly touched on later in the piece when he sets temperature to 0), temperature is not some kind of "deterministic" switch, but rather it affects the sampling distribution (which becomes more "spiky"—but is still very much a distribution).
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#7Ah... The AI learned the old HR trick: take 50% of resumes and throw them out without looking. Rationale: "we don't need unlucky losers".
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#8> I fail 65% of the time. Same exact resume, different luck. As someone who’s run hiring pipelines for technical roles in the past few years, that’s actually a fantastic number. I objectively hate saying that, but it’s true. 35% chance of elevating a technical individual to the next stage with no effort? I’ve seen as many as 100+ applicants an hour even when including a domain specific screener question. That’s 35 “s…
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Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#9> I fail 65% of the time. Same exact resume, different luck. As someone who’s run hiring pipelines for technical roles in the past few years, that’s actually a fantastic number. I objectively hate saying that, but it’s true. 35% chance of elevating a technical individual to the next stage with no effort? I’ve seen as many as 100+ applicants an hour even when including a domain specific screener question. That’s 35 “s…
Is it? Or is it a 65% chance of a resume getting ignored before a single human sees it, reducing your pipeline's likelihood of catching qualified candidates by the same? Gates that reduce resume flow-through are only useful if their reduction is correlated with quality. Otherwise they're just dragging out your hiring process or unnecessarily causing you to ultimately lower your hiring bars.
The goal for the interviewer is to have a much higher ratio of good/bad candidates after the first screening. This means the more costly time you spend on the second step has a better return.
Re: HackerRank open sourced its ATS. My resume scored 90/100. Oh wait 74. No – 88
#10An alarming number of people don't understand that LLMs work via purely stochastic processes, so I'm happy to see in-depth pieces like this. I'm looking for a job and maybe this is why it's so hard to get a callback these days: resumes are just dumped in some LLM black hole and no one really knows how it works. The author says: > temperature 0.1 — low, supposedly nudging the model toward deterministic outputs This is…
Willing to be corrected but I believe this type of automated resume filtering is illegal. Not saying it never happens but my understanding is it is not typical.