Help define what a good answer actually is

Subject experts set the standard a model is measured against: task design, expert review, and the judgement calls that decide whether an answer is right. The engagements differ sharply — some are staff roles owning a programme, some are contract or task-based contributor work — and the terms are worth reading before treating them as the same opportunity.

What these postings actually ask for

Counted from 153 of the 168 open human data roles on this board whose description this board can read, on 2026-11-10. Every figure below is a count of employers' own words. Where a requirement is not stated, that is reported as not stated rather than assumed.

Named tools. python in 49, sql in 25, label studio in 8, typescript in 8, pytorch in 7, inspect in 6, spark in 4, databricks in 2. Counted where the description names them, which understates any tool a team uses without writing it down.
Doctorate. 139 of 153 (91%) never raise one. 14 of 153 (9%) mention one, and how many of those require it is not reported here: telling a requirement from an alternative or a description of the team is a reading this board does not yet do reliably, and the page on it explains why the count was withdrawn.
Years of experience. 36 postings state a number; the median is 4, running from 1 to 7. The other 117 state none.
On call. 1 of 153 (1%) mention an on-call rotation.
Exposure to distressing material. 4 of 153 (3%) say the work involves it. Worth knowing before an interview rather than after.
Published pay. 42 of 168 open human data roles advertise a comparable annual USD base band; the rest publish nothing or publish something that is not base pay.
Remote. 58 of 168 say remote in the listing. Geography restrictions usually sit in the posting itself.
Engagement. 45 of 168 are contributor work rather than staff requisitions, and are labelled as such on the board.

See the 168 open human data roles →

Suggested by this board, not by an employer

Nothing in this section was asked for by anyone hiring. It is one editor's suggestion for demonstrating the work above, and no posting on this board requires it.

A project

Write an expert rubric and stress-test it against a second reader.

Choose a narrow, non-sensitive topic you know well. Write fifteen questions with example answers at several levels of quality. Have someone else apply your rubric, then compare the disagreements and revise the criteria. The revisions are the interesting part.

Deliverable: Share the project, your decision criteria, and a short record of what you changed after feedback.

Self-check: Can someone else reproduce your result? Are assumptions and failure cases clear? What evidence would change your conclusion?