Skill Demand Index
AI Evaluation / Data Annotation — Demand & Depth Analysis
Based on 1 scored job postings out of 4,033 total. Depth levels reflect actual proficiency tiers, not just keyword presence.
0%
Demand Rate
L1
Median Depth
100%
Gap Rate
1
Jobs Analyzed
Minimal
Most employers want AI Evaluation / Data Annotation at introductory awareness.
Overview
What is AI Evaluation / Data Annotation?
Market context for AI Evaluation / Data Annotation in the current job market
AI Evaluation / Data Annotation is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for AI Evaluation / Data Annotation typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for AI Evaluation / Data Annotation:
- •Required in 0% of all scored postings — demand is growing as more employers add it to requirements
- •Employers typically expect L1 depth — foundational knowledge with practical application
- •Most demand comes from Data Science / ML roles — 100% of all AI Evaluation / Data Annotation jobs
What L1 means in practice:
L1 (Minimal) means you can discuss the concept but haven’t used it in production. Many entry-level positions accept this.
This means employers aren't looking for someone who has used AI Evaluation / Data Annotation once or twice. They want evidence of professional application — shipped work, measurable outcomes, and the ability to operate independently.
Common skill gaps:
The gap rate of 100% means most applicants lack AI Evaluation / Data Annotation at the depth employers need. This is a real opportunity for candidates who invest in building genuine proficiency.
Which roles need AI Evaluation / Data Annotation most:
Data Science / ML positions drive 100% of demand. Skills commonly paired with AI Evaluation / Data Annotation include Google Sheets and Active Google Wallet User.
Depth Level Distribution
Proficiency Distribution
How candidates match AI Evaluation / Data Annotation requirements across 1 scored evaluations
Average depth: L1.0·Median depth: L1.0
Salary Correlation
Pay Impact
How AI Evaluation / Data Annotation affects compensation based on postings with disclosed salary data
Without AI Evaluation / Data Annotation
$140K
Median $131K
1093 jobs
Skill Demand Insight
“AI Evaluation / Data Annotation appears in 0% of all scored jobs.”
From 1 scored job postings
Skill Pairings
Commonly Paired Skills
Other skills that frequently appear alongside AI Evaluation / Data Annotation
Role Breakdown
Top Role Categories
Job categories most likely to require AI Evaluation / Data Annotation
Gap Analysis
Gap Rate Explained
How often AI Evaluation / Data Annotation is identified as a skill gap (L0–L1) in scored applications
High gap rate — most candidates are underqualified
When AI Evaluation / Data Annotation appears in a job's requirements, 100% of scored applicants received an L0 or L1 (missing or minimal).
Frequently Asked Questions
Is AI Evaluation / Data Annotation in demand in 2026?
Yes. AI Evaluation / Data Annotation appears in 0% of scored job postings on ShouldApply, making it a growing skill in the current market. Based on 1 analyzed jobs, demand is steady across multiple role types.
What level of AI Evaluation / Data Annotation do most jobs require?
The median required depth is L1. Many positions accept basic to intermediate proficiency.
Does knowing AI Evaluation / Data Annotation increase salary?
Salary data for AI Evaluation / Data Annotation is still accumulating.
What other skills pair with AI Evaluation / Data Annotation?
The most common pairings are Google Sheets, Active Google Wallet User, Linked Payment Method & Passes, Plaid Account / Connectivity, Gemini or Generative AI Tools. Strengthening these alongside AI Evaluation / Data Annotation improves your fit across more positions.
What roles need AI Evaluation / Data Annotation the most?
Top roles: Data Science / ML. Data Science / ML positions have the highest demand at 100% of all AI Evaluation / Data Annotation jobs.
How do I improve my AI Evaluation / Data Annotation level?
L1→L2: online courses and personal projects. L2→L3: daily professional use and shipped work. L3→L4: mentoring others and optimizing processes. L4→L5: architecture decisions, open source contributions, or published work.
See how you stack up against AI Evaluation / Data Annotation job requirements
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Analyze my AI Evaluation / Data Annotation gaps →See how your depth compares to what employers actually require
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