dataset creation jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, dataset creation appears in 75 job postings indexed by Skillenai over the past 90 days — AI Quality Evaluator has the most postings mentioning dataset creation.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
75
Top role · 20.0% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about dataset creation

+Is dataset creation in demand in 2026?

Yes. dataset creation appears in 75 job postings indexed by Skillenai over the 90 days ending 2026-09-30. AI Quality Evaluator accounts for the most postings mentioning dataset creation (20.0% of all postings mentioning dataset creation).

+What jobs require dataset creation?

According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning dataset creation are Data Labeling Analyst (23.1% of that role’s postings mention dataset creation), AI Benchmark Engineer (22.7% of that role’s postings mention dataset creation), Applied ML Engineer (9.5% of that role’s postings mention dataset creation).

+What skills are commonly paired with dataset creation?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), dataset creation most often appears alongside data labeling, Python, quality assurance, data annotation, machine learning.

+Where is dataset creation most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring dataset creation are San Francisco, Foster City, Amsterdam, Berlin, London, according to the Skillenai jobs index.

+How can I keep up with new dataset creation content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning dataset creation alongside the jobs index. You can subscribe to a daily email digest of new dataset creation content from your Skillenai account.

+Which skills come before and after dataset creation?

The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.

Weekly indexed postings requiring dataset creation — last 90 days

Career paths around dataset creation

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before dataset creation

Before dataset creationCNN (Convolutional Neural Network) → dataset creation: 1 observed employer moves with this skill pairclinical trial → dataset creation: 1 observed employer moves with this skill pairmachine learning models → dataset creation: 1 observed employer moves with this skill pairthermal imaging processing classifiers → dataset creation: 1 observed employer moves with this skill pairdatasetcreationCNN (Convolutional Neural Network): 1 movesCNN (ConvolutionalNeural Network)1 movesclinical trial: 1 movesclinical trial1 movesmachine learning models: 1 movesmachine learningmodels1 movesthermal imaging processing classifiers: 1 movesthermal imagingprocessingclassifiers1 moves

Skills after dataset creation

After dataset creationdataset creation → ML techniques: 1 observed employer moves with this skill pairdatasetcreationML techniques: 1 movesML techniques1 moves
How to read this chart · view counts

Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.

The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.

Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.

Observed connections and move counts
ConnectionMoves
Before: CNN (Convolutional Neural Network)1
Before: clinical trial1
Before: machine learning models1
Before: thermal imaging processing classifiers1
After: ML techniques1

Roles most likely to require dataset creation

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Data Labeling Analyst623.1%
AI Benchmark Engineer522.7%
Applied ML Engineer29.5%
AI Training Specialist12.6%
C++ Software Engineer12.1%
ML Research Engineer12.1%
Researcher11.6%
Research Engineer30.5%
Machine Learning Engineer80.3%
AI Trainer10.3%

Roles with the most dataset creation postings

RolePostings mentioning skillShare of skill postings
AI Quality Evaluator1520.0%
Machine Learning Engineer810.7%
Data Labeling Analyst68.0%
AI Benchmark Engineer56.7%
Research Engineer34.0%
Software Engineer34.0%
AI Quality Specialist22.7%
Analytics Assistant Manager22.7%
Applied ML Engineer22.7%
Client Success Director22.7%

Top companies posting jobs requiring dataset creation

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring dataset creation
CompanyPostings · 90 days
Canva15
Zoox6
Welo Data4
OpenBrain4
Telus3
Lilt-production3
HumanSignal3
Weloglobal2
OpenAI2
Spotify2

Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.

Top metros hiring for dataset creation

NamePostingsShare
San Francisco912.0%
Foster City68.0%
Amsterdam34.0%
Berlin34.0%
London34.0%
New York City34.0%
Bangkok22.7%
Taipei22.7%
Bellevue11.3%

Skills commonly paired with dataset creation

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning dataset creation by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s dataset creation postings by all dataset creation postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). An adjusted trend is not shown because comparable posting coverage is insufficient.

source
Skillenai jobs index, deduplicated daily
entity_id
bcf5f6e9922bbb79
data_as_of
2026-09-30
window_days
90
Hiring engineers who use dataset creation?

The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index