Finance
Not included unless you switch them on: 328,800 postings from Fortune 500 career sites and 68,167 postings from small-employer job boards and 14,055 postings from US federal jobs, collected since 27 September 2026. The published figures stay on the panel they have always used.
How Finance relates to the other programs
5,063 of the 147,150 postings in the United States in the last 90 days count toward Finance (3.4%), the 6th largest of the 11 programs. 4,119 count toward it alone; 944 also count toward another program. 22.3% are AI-related, against 34.8% across all postings: the 10th highest of the 10 programs with enough postings to say.
Finance is the large circle. Each small circle overlaps it in proportion to how much of its domain knowledge it shares with Finance: the most alike program has 80% of its area inside, a program with half that similarity half as much, and one that shares nothing just touches. Around the ring, programs sit next to the ones they share most with. The number in each circle is the exact figure; every circle opens that program.
Most alike on domain knowledge
- Business Management53% in common
Sales · Budgeting · Marketing · Key performance indicators (KPIs) · Data analysis and analytics
- Accounting53% in common
Budgeting · Sales · Pricing · Data analysis and analytics · Entrepreneurship
- Strategic Management47% in common
Sales · Marketing · Budgeting · Pricing · Partnerships
- Human Resource Management45% in common
Sales · Marketing · Budgeting · Partnerships · Key performance indicators (KPIs)
- Marketing45% in common
Sales · Budgeting · Marketing · Partnerships · Key performance indicators (KPIs)
- Sales44% in common
Sales · Business development · Marketing · Pricing · Budgeting
- Global Supply Chain Management44% in common
Sales · Budgeting · Pricing · Marketing · Partnerships
- Entrepreneurial Management40% in common
Sales · Business development · Marketing · Partnerships · Entrepreneurship
- Information Systems38% in common
Sales · Marketing · Budgeting · Partnerships · Data analysis and analytics
- Experience Design and Management31% in common
Marketing · Sales · Budgeting · Partnerships · Entrepreneurship
“In common” is the share of the two programs’ domain knowledge mixes that they hold together: for each item, the smaller of its two shares, summed, over the larger, summed. Items shown are the ones both programs ask for most, each held by at least 20 postings in both. Last 90 days, every geography. A posting counts toward a program when the discipline classifier assigns it there (how postings are classified).
Where Finance postings fall across the four quadrants
Each bar counts Finance postings in one quadrant, not the whole quadrant. The filled part is how many of those are AI-related. The last figure on each row turns it round: how much of that whole quadrant of the labour market Finance postings make up. Last 90 days, by real posting date. Each quadrant’s name opens it on the overview, across every program.
- Business, AI-thinthe established business majors, unchanged2,538postings17.7%AI-relatedFinance is 2.8% of all Business, AI-thin postings
- Business-deep AIan AI-in-business major2,377postings23.6%AI-relatedFinance is 6.0% of all Business-deep AI postings
- Hybrid AIan information systems major, revised for AI124postingstoo few postings for an AI shareFinance is 1.4% of all Hybrid AI postings
- Builder-deep AIa computer-science AI degree24postingstoo few postings for an AI shareFinance is 0.3% of all Builder-deep AI postings
What the four quadrants are cut on. The capabilities a posting asks for, read from its description. A role naming three or more distinct engineering capabilities has builder depth; three or more business capabilities gives business depth. Both is Hybrid, neither is AI-thin. There are four because two yes-or-no tests cross, which is what makes them quadrants rather than a list. The threshold of three is the one the source analysis used, adopted rather than reinvented so the two stay comparable.
The 5,063 postings drawn here are this program’s share of the panel: postings carrying a real posting date from the last 90 days in the United States that the discipline classifier assigns to it. A posting can count toward more than one program. Quadrants with fewer than 20 postings are left out, and AI shares are withheld below 200.
What each quadrant asks for
Ranked by how far Builder-deep AI sits from the other quadrants, not by how often the item appears. The bar is this region; the ticks are the others. An item everybody asks for tells you nothing about where you are.
This program has too few postings in Builder-deep AI for a profile: items need 20 postings and the quadrant needs 200 before a share is shown. Try another quadrant.
Shares are of postings in this region over the last 90 days, by real posting date, in the geography chosen above. These figures were fixed to the United States until 22 September 2026 and could not follow that choice; they can now.
Where these numbers come from
8,190 Finance postings have been collected in all. The figures above use 5,063 of them: the last 90 days (7,438), and of those, the ones in the United States. Each bar is one source.
- The Musea general job board, not chosen for AI2,703usedof 4,098 collected12.4%AI-related
- Remote job boardsboards listing remote roles2,116usedof 3,601 collected28.8%AI-related
- Employer career siteschosen because these employers post AI work244usedof 449 collected74.6%AI-related
- Hacker Newsmonthly hiring threads, mostly without a usable date or place0usedof 42 collected
The sources ask for AI at very different rates because they were collected for different reasons, so the 22.3% AI share at the top of the page is a mix of them and moves with that mix. Compare sources side by side rather than reading the pooled figure as the market’s. How each source is collected, and why they are never pooled for the market figures, is under the four sub-corpora on the research page.
What this page cannot tell you yet
No job titles from this program
The rules matching postings to this discipline were written without input from the people who know where these graduates go. Titles you supply become candidate rules, measured against the corpus before anything is published.
No employers from this program
None of the employers who actually hire your graduates have been named, so the panel can only describe firms that happen to post on the boards already collected. Named employers are resolved to their public job feed and collected directly.
Two things from you change all of the above. The job titles your graduates commonly take, and the employers who commonly hire them. Titles become candidate classifier rules; employers become collection targets, deduplicated across every program so the ones several of you name independently get resolved first.
Sign in to add them. Everything you enter is stored as a claim from your program, never merged into the posting evidence, and shown with your program named beside it.