How many people apply to a single job posting?
There are lots of reasons given for why finding a job in 2026 is so difficult: "AI", "hiring freezes" and continued shedding from Covid-era rampant hiring sprees. But what does that mean for a job seeker, practically? As a math guy, I sometimes have the need to quantify better what we're dealing with so we're not just working in the dark.
I would guess a remote, full-time role in tech or adjacent spaces at a company that has at least 2/5 stars on Glassdoor and pays decently (yes, the bar is on the floor) can probably receive roughly 2,000 applicants in the first 2–3 days of posting. If the position is not remote, then probably less (depends on the metro area), if the company has a reputation for being a good place to work, then possibly more — but regardless I think we can agree that good roles are highly competitive. These numbers are just based on raw data I've seen on LinkedIn, but let's do some rough math.
(1) A good number of these 2,000 applicants are probably unqualified. Next time you're on LinkedIn and looking at a say, mid-level position, look at how many candidates LinkedIn claims are "entry-level" — usually 30–40% at least. Consider also candidates who are ineligible, maybe even not real; we could conservatively say we may have 200 applicants who are somewhat qualified. So a priori, if you consider yourself an average applicant among this pool — you're looking at 1/200 odds. But it gets worse.
Do companies already have someone in mind?
(2) Your 1/200 odds assumes that all qualified applicants have equal odds. And the poorly-kept secret is that this is not how it works, at all. Firstly, a lot of jobs already have someone in mind — either internally (i.e. a promotion or internal transfer) or externally (manager's report from a past job, a teammate's buddy, etc.). The prevalence of this is not clear — companies generally lack motivation to do research in how many of their job postings are fake. I think it's reasonable to guess at least 50–60% of positions have some "warm" leads, probably higher at better companies or on better teams. If you assume your chance at getting a job where these "warm leads" are present is diminished by, say, 50% then your overall chances diminish by ~25%, so let's say your 1/200 odds are more like 1/250, and I think this is being generous. Let's not get into jobs that get pulled due to new hiring freezes, budget concerns, or postings that were just there for optics or other reasons.
Why qualified applicants still get rejected
So at the individual job level, let's say your chances are 1/250. Now employers get picky as they are flooded with applicants. The idea that "you can learn that on the job" doesn't make sense when you can find someone skilled (at least on paper) in any given technology or desired industry by tomorrow. Recruiters may also be picky in other ways — e.g. current witch hunts for AI-generated resumes. According to Forbes, about 75% of recruiters throw out resumes that appear to be AI-generated. This has created a shift in how resumes and bullet points are written: phrases like "results-driven", "Spearheaded X", etc. are discouraged for this reason. The irony is that this verbiage was considered industry-standard before AI (the dominance of this verbiage was the reason it was picked up by these large language models in the first place). Not to mention AI has been used to filter out applicants for years among other uses in the recruiting process.
How to apply to more jobs without sacrificing quality
So what can you do? When your odds for any single position is so low and competition so high, you need two things that are naturally pitted against each other: (1) Volume — you need to apply to lots of jobs and (2) Quality — your resume needs to be good enough that it makes it through ATS and has enough direct relevance to the job to be successful. I go deeper on how to actually pull this off in how to get a job without connections — including the exact approach I used to beat 2,000+ applicants.