Ask HN: Why don't employers post an applicant-to-job ratio? - keenmaster
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muzani
I think it's mostly because the statistics don't tell the story. I've been on
the hiring side for 3 companies. We'd take the first non-idiotic person who
applies.

If you're the kind of person to be a friend, you'd likely be hired. If you're
the kind of stranger looking for a job, you'd be unlikely to be hired. If
you're the kind of person to hang out on HN or some Facebook/Slack meme
groups, we couldn't afford your salary.

Out of that, it would be roughly 90% of applicants who don't qualify, 5% who
we can't afford, and somewhere in between which we just settle for. Many new
graduates can't do FizzBuzz, many people who apply for a senior position can't
reverse a linked list.

~~~
keenmaster
“We'd take the first non-idiotic person who applies.”

I think it would still help for a company like that to display stats. For
example, if you’re a qualified candidate who is applying early, you’d see an
abnormally high probability of callback. If you’re an unqualified candidate,
you’d see a very low probability of callback. I mentioned that ML can help
calculate these probabilities. In addition, I think it might help for
companies to secretly encode “hard” job requirements. Most requirements are in
fact soft, but the applicant never knows which is which. If they don’t meet a
hard requirement, they should see a 0% probability of callback. Full stop. ML
would do a good job of assigning importance weights to each of the
requirements which aren’t encoded as “hard,” but it would start from weights
provided by the employer when there isn’t enough data.

~~~
tom_b
But stats like that also can signal being over-selective.

I would gently suggest that it is a mistake to think in terms of unqualified
vs highly-qualified candidates and ML for "callback probability". I don't want
a good, but not FANG-level, candidate to NOT apply for our standard software
engineer opening just because 74 people already did.

Why? We had 60+ candidates for a recent posting for a junior developer role
with some experience - think 1-2 years or some good school projects. Somewhere
around 45-50 of those applicants were easily _HARD-FLAGGED_ don't interview at
all after a quick cover-letter and resume review by a technical person using a
rubric. That rubric was scoped only to weed out applicants with absolutely no
meaningful experience.

While I also hate the laundry-list approach for job listings (Must Have:
Expert Java and C#, Spring ORM and ActiveRecord skills with deep understanding
of React internals), I think the best way to attack that is with a short, but
focused cover letter. That should include a short paragraph or two about a
candidate's hands-on experience and speculate how their experience might apply
to the position. I guess what I am driving at is that this idea of ML
assigning importance weights to "soft" vs "hard" requirements is, at best,
just another low-value signal in job postings that are already full of low-
value signal.

~~~
keenmaster
Just like on your LinkedIn profile, there would be way more than a simple list
of keywords and skills. The keywords would be part of a full profile which
includes universities/degrees, certificates, years of experience,
accomplishments, etc...some of which are easier for an ML to train on than
others, but my point is those are stronger signals than “Java: Yes.” If there
is residual fuzziness in the process, the platform can add skill tests (taken
at a test center) that can get listed on your profile.

A third party ecosystem of skill tests could emerge, some of which would be
more prestigious/respectable than others. Some would have a binary output, and
some would give you a score that is benchmarked against the population of test
takers. This would only really be necessary for more technical skills. I’m not
talking about rinky dinky khaki cubicle test centers. I’m talking about new
age corporations with $1B market cap that develop an unparalleled ability to
assess skills so that corporate HR departments don’t have to. These testing
companies would be part of the ecosystem developed by the theoretical ideal,
statistically-oriented, applicant friendly job platform that I’m talking
about.

------
keenmaster
Example with made up numbers:

Google Software Engineer I - 100 total jobs, 2000 applicants (click here for a
breakout by region). Based on historical data and the current applicant pool,
you have a 8% chance of scoring an interview if you apply to [All Locations]
and 5% if you apply to Mountain View only.

Aerojet Rocketdyne Inc. Software Engineer I - 10 total jobs, 150 applicants
(Sacramento only). Based on historical data and the current applicant pool,
you have a 20% chance of scoring an interview.

I know that withholding such statistics is advantageous for the employer and
maximizes the number of applications. However, my question is directed more at
job platforms like LinkedIn. At most, they only show the number of
applications. When I apply, I don't have the faintest idea whether I'll get a
response or whether my application will go into a black hole. I believe a more
applicant-friendly job platform, which publishes more statistics, aggressively
penalizes outdated/lame listings, and incentivizes updates from the employer
will attract more applicants. Those applicants will in turn attract more
companies, so on and so forth.

The job search grind is a major unsolved problem. Unless you have the most
fungible skillset and level of experience, applying to jobs is soul crushing.
We don't even have read receipts for resumes. There are so many low hanging
fruit which haven't been touched by the major job platforms. People are not
opposed to long job applications. What is deeply problematic is that there
doesn't seem to be a correlation between the length/redundancy of a job
application and your chance of getting a callback. With ML, it doesn't seem
impossible for LinkedIn to modify its platform such that it can give you
reasonable assurance as to your chance of getting a callback. Solving this
issue will be nothing more of revolutionary. It would single-handedly make the
economy more dynamic. I'd love to hear an informed take on this issue though,
maybe I'm missing a key constraint.

------
PaulHoule
How is that useful?

If they are getting much less than one applicant per job it's clear they are
doing something wrong.

Jobs get spam applications and it might be that anything from 50-90% don't get
a second glance; if you are a fit for the job that won't be you, your odds
will be much higher.

------
JSeymourATL
> When I apply, I don't have the faintest idea whether I'll get a response or
> whether my application will go into a black hole.

STOP applying to positions immediately.

Every Bozo jobseeker is applying to those posts.

And worse still, the candidates are sorted and selected by Flunky HR types.

Instead, consider your target audience.

ASK: Who is the guy/gal you can most help? What are their title(s)?

Think - CTO/CIO, VP or Director of Engineering

Where do they sit? What companies?

Now, hop on Linkedin.

Sort for individual profiles of people you can help.

Reach out to them directly. Engage in a live conversation.

Do this 100 times.

You will find competing opportunities.

~~~
muzani
The gatekeepers are there for a reason. Unless you already know someone who
sits high in a company, this won't work. Every Bozo jobseeker does this on
LinkedIn too, and they're usually worse than the ones who follow the process.

~~~
JSeymourATL
> The gatekeepers are there for a reason.

Self-Limiting thinking.

Unless you're a rules, systems, and process guy.

This is a real life Kobayashi Maru test.

~~~
keenmaster
“This is a real life Kobayashi Maru test.”

Do you know empirically that that’s the ideal way to screen candidates?
Because that would be the only good reason for so many companies to hire in
that manner. There are many great engineers who, precisely because of the
traits that make them great, would “fail” that Kobayashi Maru test and settle
for a suboptimal role. Not only do they lose out on experience befitting of
their aptitude, but the company loses out on the best candidate, and the
economy loses out on the surplus created by ideal labor matching.

~~~
JSeymourATL
> ideal labor matching.

The system is NOT designed for ideal labor matching.

Not unlike the Test.

The job-seeker (applicant) and Employer are working at cross-purposes.

Incidentally, many Hiring Executives understand this problem.

And are often open to dialoguing with people trying to circumvent the HR black
hole.

Manage or Be Managed is the proposition.

Either hunt for work (people you can help)

or passively hope someone will notice you.

~~~
keenmaster
The job search process, as it stands, is another high entropy game in a life
full of games. Many companies have reached the heights of success by reducing
or eliminating one of those games. Ebay is one example - it takes out all the
posturing and dumb games involved in selling an illiquid item. As a result of
Ebay, many more of those items are sold, for higher prices, more quickly, and
to the people that ascribe the highest value to them.

Sure, the job search "game" cannot be completely eliminated. There will always
be some fuzziness. However, the fuzziness can be greatly reduced on both
sides, and that would be immensely valuable. You have way more faith in the
value of the current job search game than I do.

------
codegeek
Linkedin job postings do show the number of applicants for a job.

~~~
keenmaster
Sure, but LinkedIn doesn't always show you the true applicant-to-job ratio.
For many great jobs at large companies, especially at lower levels, there are
many "seats." LinkedIn doesn't tell you how many Software Engineer I's Google
is hiring.

Moreover, I think LinkedIn could do a better job of presenting other
statistics to job candidates and reducing noise on the platform. They have
done little to mitigate the feeling that your resume is most likely to
disappear into a black hole. When I apply to a job, I want a good
approximation of how likely it is that I even get a response. As it stands,
companies have zero incentive not to waste your time, and that is actually bad
for the both of you. There is more discussion on this below.

------
gshdg
What value would the employer get from providing that info?

~~~
muzani
It's a lot like posting response rate. For one thing, it's a polite rejection.
Politeness encourages more applicants. Not having a black hole will also
encourage applicants to complete the process. There's also some
fatigue/anxiety as part of a long process, which will affect the requested
salary or acceptance - someone is more likely to accept a well paid job with a
pleasant process than a well paid job with a tiresome process.

YC, Toptal, and many universities post their acceptance rate, and it's only
proven a good thing. The ambitious ones will be encouraged to try even with a
low acceptance rate.

