Skill Demand Index

ML frameworks (scikit-learn, TensorFlow or PyTorch) — 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

L3

Median Depth

0%

Gap Rate

1

Jobs Analyzed

L3100% of postings

Proficient

Most employers want ML frameworks (scikit-learn, TensorFlow or PyTorch) at hands-on daily use, not textbook knowledge.

Overview

What is ML frameworks (scikit-learn, TensorFlow or PyTorch)?

Market context for ML frameworks (scikit-learn, TensorFlow or PyTorch) in the current job market

ML frameworks (scikit-learn, TensorFlow or PyTorch) is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for ML frameworks (scikit-learn, TensorFlow or PyTorch) typically want candidates who can demonstrate real proficiency, not just surface awareness.

What the data shows for ML frameworks (scikit-learn, TensorFlow or PyTorch):

  • Required in 0% of all scored postingsdemand is growing as more employers add it to requirements
  • Employers typically expect L3 depthhands-on proficiency, not surface awareness
  • Most demand comes from Data Science / ML roles100% of all ML frameworks (scikit-learn, TensorFlow or PyTorch) jobs

What L3 means in practice:

L3 (Proficient) means daily professional use. You should be able to work independently with ML frameworks (scikit-learn, TensorFlow or PyTorch) without needing supervision or constant guidance.

This means employers aren't looking for someone who has used ML frameworks (scikit-learn, TensorFlow or PyTorch) 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 0% means most candidates have adequate ML frameworks (scikit-learn, TensorFlow or PyTorch) proficiency. To stand out, aim for L4-L5 depth with concrete evidence.

Which roles need ML frameworks (scikit-learn, TensorFlow or PyTorch) most:

Data Science / ML positions drive 100% of demand. Skills commonly paired with ML frameworks (scikit-learn, TensorFlow or PyTorch) include Python (pandas, NumPy) and SQL (advanced query design and optimization).

Depth Level Distribution

Proficiency Distribution

How candidates match ML frameworks (scikit-learn, TensorFlow or PyTorch) requirements across 1 scored evaluations

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

Average depth: L3.0·Median depth: L3.0

Salary Correlation

Pay Impact

How ML frameworks (scikit-learn, TensorFlow or PyTorch) affects compensation based on postings with disclosed salary data

Without ML frameworks (scikit-learn, TensorFlow or PyTorch)

$140K

Median $131K

1093 jobs

Skill Demand Insight

ML frameworks (scikit-learn, TensorFlow or PyTorch) appears in 0% of all scored jobs.”

From 1 scored job postings

Skill Pairings

Commonly Paired Skills

Other skills that frequently appear alongside ML frameworks (scikit-learn, TensorFlow or PyTorch)

Role Breakdown

Top Role Categories

Job categories most likely to require ML frameworks (scikit-learn, TensorFlow or PyTorch)

Gap Analysis

Gap Rate Explained

How often ML frameworks (scikit-learn, TensorFlow or PyTorch) is identified as a skill gap (L0–L1) in scored applications

0%

Very low gap rate — candidates generally have this skill

When ML frameworks (scikit-learn, TensorFlow or PyTorch) appears in a job's requirements, 0% 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 ML frameworks (scikit-learn, TensorFlow or PyTorch) in demand in 2026?

Yes. ML frameworks (scikit-learn, TensorFlow or PyTorch) 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 ML frameworks (scikit-learn, TensorFlow or PyTorch) do most jobs require?

The median required depth is L3. Most roles expect intermediate competency — independent work without supervision.

Does knowing ML frameworks (scikit-learn, TensorFlow or PyTorch) increase salary?

Salary data for ML frameworks (scikit-learn, TensorFlow or PyTorch) is still accumulating.

What other skills pair with ML frameworks (scikit-learn, TensorFlow or PyTorch)?

The most common pairings are Python (pandas, NumPy), SQL (advanced query design and optimization), 5+ years data science, Spark / PySpark, Deploying, monitoring, and maintaining models. Strengthening these alongside ML frameworks (scikit-learn, TensorFlow or PyTorch) improves your fit across more positions.

What roles need ML frameworks (scikit-learn, TensorFlow or PyTorch) the most?

Top roles: Data Science / ML. Data Science / ML positions have the highest demand at 100% of all ML frameworks (scikit-learn, TensorFlow or PyTorch) jobs.

How do I improve my ML frameworks (scikit-learn, TensorFlow or PyTorch) 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 ML frameworks (scikit-learn, TensorFlow or PyTorch) job requirements

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