The Most Common Job Title in the Market Covers 0.2% of It

Share of all 247,242 active postings carrying each exact title, at the 2026-08-13 16:28 UTC snapshot. These are the twelve largest title groups in the entire corpus. The point of the chart is the axis: the biggest job title in the market is one fifth of one percent of it.

Distinct exact titles divided by active postings, computed inside each source separately, at the 2026-08-13 16:28 UTC snapshot. A value of 1.00 would mean every posting on that source has a title unique within it. himalayas is highlighted because it is 44.1% of the corpus and therefore the obvious candidate for creating the effect single-handedly; at 0.79 it is below the corpus-wide pattern rather than above it, so it is not the cause. The two lowest rows, reed and adzuna, are consumer-facing aggregators that normalise titles before republishing them, which is what a normalised feed looks like and what the direct employer feeds above them are not doing.

Source: Seeker job corpus, 247,242 active job postings, snapshot 2026-08-13. seekerscore.com/insights/job-titles-nobody-else-uses-2026

The distribution has almost no middle

Group 247,242 postings by exact title and you get 191,637 groups. 174,127 of those groups contain exactly one posting, which means 70.4% of the corpus is titles used once. At the other end, only 877 titles are used ten or more times, and together they cover 29,618 postings, 12.0% of the market. Only 48 titles are used a hundred times or more, covering 4.1%. There is essentially no middle: a title is either shared by a handful of postings or by none at all. The named roles everyone thinks in terms of are real but tiny as exact strings. 'Software engineer' as an exact title is 496 postings out of 247,242.

Why the titles are unique, which is not the same as arbitrary

Uniqueness is mostly manufactured by what employers append. Of the 174,127 titles used exactly once, 129,099 (74.1%) contain a bracket, comma, slash, pipe or hyphen, 32,024 (18.4%) run longer than sixty characters and 16,207 (9.3%) contain a digit. These are titles like a role name followed by a location, a department, a level code or a requisition number. That matters for how you respond to it. The underlying role is usually ordinary; the string is not. So the failure mode of a title search is not that the market is full of exotic jobs, it is that an ordinary job is wearing a string that only one posting in the world uses, and an exact-match query or a saved alert cannot see through it.

It is not one job board's formatting habit

The obvious rival explanation is that one large feed with messy titles is dragging the whole corpus. himalayas is 44.1% of the active corpus, so it is the candidate. It is not the cause. Computed inside each source separately, distinct titles per posting is 0.98 on kaiser, 0.96 on google, 0.91 on apple, amazon and ashby, 0.90 on oracle_cloud, 0.89 on workday and greenhouse, and 0.79 on himalayas. The single biggest source is the least unique of the direct employer feeds, not the most. The genuinely low rows are reed at 0.47 and adzuna at 0.52, both consumer aggregators that clean titles before republishing. So the pattern is strongest exactly where postings come straight from the employer's own system, which is where most of the market lives.

What this changes about how you search

Three consequences follow directly from the numbers. First, a saved job alert on an exact title is close to useless: the best case, 'data engineer', would have alerted you to 498 of 247,242 postings. Second, adding words to a search makes it worse at a rate people underestimate, because every appended qualifier moves you toward the 70.4% of the market whose titles are one-offs. Search shorter, not more precisely. Third, and most useful, filter on the things that are actually shared between postings rather than on the title. Skills are, employers are, seniority is, location is. This is the same conclusion our earlier title-families page reached from the opposite direction: it found that 1,075 distinct title strings all describe one software engineering role, and this page finds that 70.4% of all postings use a string nobody else uses. Those are two views of one problem.

How we measured this, and what we did not do

One snapshot of the jobs table at 2026-08-13 16:28 UTC, 247,242 active rows, every one of which carries a title. Titles were lowercased and had surrounding whitespace stripped, and then grouped by exact string equality. That is the entire transformation. Deliberately, no classifier, no stemming, no fuzzy matching and no title-family model was involved, because the question is what a literal search box would do, and a literal search box does exact matching on the string as written. This is the counterpart to our job-title-variations page, which uses a model to group titles into families and answers the different question of how many names one role can have. Two things this page cannot tell you: how many of the 191,637 titles are genuinely different jobs, which needs exactly the classifier we excluded here, and whether the employer or the applicant tracking system added the suffix, since we see the title only after it has been published.

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