Skill Demand Index

Machine Learning/NLP — Demand & Depth Analysis

Based on 1 scored job postings out of 4,003 total. Depth levels reflect actual proficiency tiers, not just keyword presence.

0%

Demand Rate

L1

Median Depth

100%

Gap Rate

1

Jobs Analyzed

L1100% of postings

Minimal

Most employers want Machine Learning/NLP at introductory awareness.

Overview

What is Machine Learning/NLP?

Market context for Machine Learning/NLP in the current job market

Machine Learning/NLP is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for Machine Learning/NLP typically want candidates who can demonstrate real proficiency, not just surface awareness.

What the data shows for Machine Learning/NLP:

  • Required in 0% of all scored postingsdemand is growing as more employers add it to requirements
  • Employers typically expect L1 depthfoundational knowledge with practical application
  • Most demand comes from Data Science / ML roles100% of all Machine Learning/NLP 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 Machine Learning/NLP 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 Machine Learning/NLP at the depth employers need. This is a real opportunity for candidates who invest in building genuine proficiency.

Which roles need Machine Learning/NLP most:

Data Science / ML positions drive 100% of demand. Skills commonly paired with Machine Learning/NLP include Experiment Design and Product Collaboration.

Depth Level Distribution

Proficiency Distribution

How candidates match Machine Learning/NLP requirements across 1 scored evaluations

L0 — Missing
0% (0)
L1 — Minimal
100% (1)
DOMINANT
L2 — Basic
0% (0)
L3 — Proficient
0% (0)
L4 — Advanced
0% (0)
L5 — Expert
0% (0)

Average depth: L1.0·Median depth: L1.0

Salary Correlation

Pay Impact

How Machine Learning/NLP affects compensation based on postings with disclosed salary data

Without Machine Learning/NLP

$139K

Median $131K

1077 jobs

Skill Demand Insight

Machine Learning/NLP appears in 0% of all scored jobs.”

From 1 scored job postings

Skill Pairings

Commonly Paired Skills

Other skills that frequently appear alongside Machine Learning/NLP

Role Breakdown

Top Role Categories

Job categories most likely to require Machine Learning/NLP

Gap Analysis

Gap Rate Explained

How often Machine Learning/NLP is identified as a skill gap (L0–L1) in scored applications

100%

High gap rate — most candidates are underqualified

When Machine Learning/NLP appears in a job's requirements, 100% of scored applicants received an L0 or L1 (missing or minimal).

A high gap rate signals strong hiring leverage for candidates who have it. A low gap rate means the skill is table stakes: not having it is a disqualifier.

Frequently Asked Questions

Is Machine Learning/NLP in demand in 2026?

Yes. Machine Learning/NLP 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 Machine Learning/NLP do most jobs require?

The median required depth is L1. Many positions accept basic to intermediate proficiency.

Does knowing Machine Learning/NLP increase salary?

Salary data for Machine Learning/NLP is still accumulating.

What other skills pair with Machine Learning/NLP?

The most common pairings are Experiment Design, Product Collaboration, SQL, Data Science, Python. Strengthening these alongside Machine Learning/NLP improves your fit across more positions.

What roles need Machine Learning/NLP the most?

Top roles: Data Science / ML. Data Science / ML positions have the highest demand at 100% of all Machine Learning/NLP jobs.

How do I improve my Machine Learning/NLP 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 Machine Learning/NLP job requirements

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