Skill Demand Index
NLP/Information Extraction — Demand & Depth Analysis
Based on 2 scored job postings out of 3,786 total. Depth levels reflect actual proficiency tiers, not just keyword presence.
0.1%
Demand Rate
L2
Median Depth
50%
Gap Rate
2
Jobs Analyzed
Minimal
Most employers want NLP/Information Extraction at introductory awareness.
Overview
What is NLP/Information Extraction?
Market context for NLP/Information Extraction in the current job market
NLP/Information Extraction is required in 0.1% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for NLP/Information Extraction typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for NLP/Information Extraction:
- •Required in 0.1% of all scored postings — demand is growing as more employers add it to requirements
- •Employers typically expect L2 depth — foundational knowledge with practical application
- •Most demand comes from Data Science / ML roles — 100% of all NLP/Information Extraction jobs
What L2 means in practice:
L2 (Basic) means you’ve built small things with NLP/Information Extraction — personal projects or bootcamp work. Employers accept this for junior roles.
This means employers aren't looking for someone who has used NLP/Information Extraction 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 50% means most applicants lack NLP/Information Extraction at the depth employers need. This is a real opportunity for candidates who invest in building genuine proficiency.
Which roles need NLP/Information Extraction most:
Data Science / ML positions drive 100% of demand. Skills commonly paired with NLP/Information Extraction include Python and Data Science Experience.
Depth Level Distribution
Proficiency Distribution
How candidates match NLP/Information Extraction requirements across 2 scored evaluations
Average depth: L2.0·Median depth: L2.0
Salary Correlation
Pay Impact
How NLP/Information Extraction affects compensation based on postings with disclosed salary data
Without NLP/Information Extraction
$139K
Median $130K
979 jobs
Skill Demand Insight
“NLP/Information Extraction appears in 0.1% of all scored jobs.”
From 2 scored job postings
Skill Pairings
Commonly Paired Skills
Other skills that frequently appear alongside NLP/Information Extraction
100%
co-occurrence
100%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
Role Breakdown
Top Role Categories
Job categories most likely to require NLP/Information Extraction
Gap Analysis
Gap Rate Explained
How often NLP/Information Extraction is identified as a skill gap (L0–L1) in scored applications
Moderate gap rate — many candidates lack this skill
When NLP/Information Extraction appears in a job's requirements, 50% of scored applicants received an L0 or L1 (missing or minimal).
Frequently Asked Questions
Is NLP/Information Extraction in demand in 2026?
Yes. NLP/Information Extraction appears in 0.1% of scored job postings on ShouldApply, making it a growing skill in the current market. Based on 2 analyzed jobs, demand is steady across multiple role types.
What level of NLP/Information Extraction do most jobs require?
The median required depth is L2. Many positions accept basic to intermediate proficiency.
Does knowing NLP/Information Extraction increase salary?
Salary data for NLP/Information Extraction is still accumulating.
What other skills pair with NLP/Information Extraction?
The most common pairings are Python, Data Science Experience, Productionizing ML models, Knowledge Graphs/Graph-Based ML, Entity Resolution/Relationship Discovery. Strengthening these alongside NLP/Information Extraction improves your fit across more positions.
What roles need NLP/Information Extraction the most?
Top roles: Data Science / ML. Data Science / ML positions have the highest demand at 100% of all NLP/Information Extraction jobs.
How do I improve my NLP/Information Extraction 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 NLP/Information Extraction job requirements
ShouldApply scores your profile against each skill at the depth level jobs actually need.
Analyze my NLP/Information Extraction gaps →See how your depth compares to what employers actually require
All Skills · Roles · Companies · Browse Jobs