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Across 981 company career pages we read in full, software engineer is the most advertised role by a wide margin, at 10,225 open postings. Second is a sales role: these companies advertise 3,910 account executive roles against 2,216 for data scientist, AI engineer and machine learning engineer combined.
161,969
Deduplicated on the product's own key, so a role posted to several boards counts once. A count of postings, not of rows in our index.
As of
Why career pages and not the whole index
Most of what we ingest is keyword-driven: we ask each board for a list of terms in a list of countries, so the role mix in those rows mirrors what we searched for. Four platforms work differently. Greenhouse, Lever, Ashby and SmartRecruiters are read a company at a time, whole board, no query, so within that set of companies the role mix is a census.
That buys accuracy at the cost of reach. Companies on these systems skew toward technology and away from the public sector and small employers. Every number here is about these companies, not the labour market.
The ranking
| Group | Value |
|---|---|
| Software engineer | 10,225 |
| Account executive | 3,910 |
| Product manager | 2,905 |
| Designer | 2,379 |
| Project manager | 2,324 |
| Marketing manager | 1,393 |
| Data engineer | 1,144 |
| Customer success manager | 1,116 |
| Security engineer | 955 |
| Data scientist | 882 |
| Recruiter | 798 |
| AI engineer | 702 |
| Machine learning engineer | 632 |
| Accountant | 565 |
| DevOps engineer | 350 |
As of
Below software engineer, the list is less engineering than these platforms' reputation suggests. Account executive, product manager, designer and project manager take the next four places, and together they outnumber software engineer. Designer, at 2,379, outnumbers data scientist, AI engineer and machine learning engineer combined.
The data and AI roles are smaller than they sound
AI engineer has overtaken machine learning engineer as a title, 702 to 632. That looks like a change in what the job is called, and it only shows up in postings. Data engineer also outranks data scientist, 1,144 to 882.
One claim we expected to make did not survive. On a looser title match, machine learning appeared to outrank data scientist. Matching both at the same strictness reversed it, so it is not reported.
Where these roles are
| Group | Value |
|---|---|
| United States | 67,785 |
| United Kingdom | 10,544 |
| Not resolved | 8,955 |
| France | 8,627 |
| India | 8,062 |
| Germany | 6,037 |
| Canada | 5,872 |
| Brazil | 3,605 |
| Spain | 3,564 |
| Netherlands | 2,714 |
As of
The United States takes 41.9% of the census, the United Kingdom 6.5%, France 5.3% and India 5.0%. 5.5% of postings do not carry enough location text to place. We show that share because dropping it would inflate every share below it.
Why there is no "what changed since last month"
Our index's make-up moves with our own crawling. A new source going live looks exactly like a hiring surge, and so does discovery adding a batch of companies to this census. So this post is a baseline. The queries, title patterns and row floors are declared in the post itself, and the next edition runs the same cuts, which is when movement becomes reportable.
Methodology
Source. Every posting from Greenhouse, Lever, Ashby and SmartRecruiters in the index on the day of the pull, read a company at a time with no search term. Keyword-driven sources are excluded, because their mix reflects our keyword list.
Counting. Collapsed on the product's own dedupe key, so each figure counts postings, not index rows. Roles are matched by title pattern, so one posting can count under more than one role. A role or country under the row floor is left out rather than printed.
Limits. Which companies are in the set is decided by our discovery, which is not random and skews toward technology. No liveness check has been run on this subset, so a posting counted here may already be closed.
Run the search yourself
Every figure here comes from the jobs Jobzyl has indexed, and carries the date it was pulled.
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