Skill Demand Index
Based on 1 scored job postings out of 2,449 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 TensorFlow, PyTorch, scikit-learn at introductory awareness.
Overview
Market context for TensorFlow, PyTorch, scikit-learn in the current job market
TensorFlow, PyTorch, scikit-learn is required in 0% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for TensorFlow, PyTorch, scikit-learn typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for TensorFlow, PyTorch, scikit-learn:
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 TensorFlow, PyTorch, scikit-learn 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 TensorFlow, PyTorch, scikit-learn at the depth employers need. This is a real opportunity for candidates who invest in building genuine proficiency.
Which roles need TensorFlow, PyTorch, scikit-learn most:
Software Engineering positions drive 100% of demand. Skills commonly paired with TensorFlow, PyTorch, scikit-learn include Bachelor's Degree.
Depth Level Distribution
How candidates match TensorFlow, PyTorch, scikit-learn requirements across 1 scored evaluations
Average depth: L1.0·Median depth: L1.0
Salary Correlation
How TensorFlow, PyTorch, scikit-learn affects compensation based on postings with disclosed salary data
Without TensorFlow, PyTorch, scikit-learn
$137K
Median $130K
454 jobs
Skill Demand Insight
“TensorFlow, PyTorch, scikit-learn appears in 0% of all scored jobs.”
From 1 scored job postings
Skill Pairings
Other skills that frequently appear alongside TensorFlow, PyTorch, scikit-learn
Role Breakdown
Job categories most likely to require TensorFlow, PyTorch, scikit-learn
Gap Analysis
How often TensorFlow, PyTorch, scikit-learn is identified as a skill gap (L0–L1) in scored applications
High gap rate — most candidates are underqualified
When TensorFlow, PyTorch, scikit-learn appears in a job's requirements, 100% of scored applicants received an L0 or L1 (missing or minimal).
Yes. TensorFlow, PyTorch, scikit-learn 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.
The median required depth is L1. Many positions accept basic to intermediate proficiency.
Salary data for TensorFlow, PyTorch, scikit-learn is still accumulating.
The most common pairings are Bachelor's Degree, Early-Stage Startup Experience, Programming Skills, Machine Learning Engineering, SLMs (Small Language Models). Strengthening these alongside TensorFlow, PyTorch, scikit-learn improves your fit across more positions.
Top roles: Software Engineering. Software Engineering positions have the highest demand at 100% of all TensorFlow, PyTorch, scikit-learn jobs.
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 TensorFlow, PyTorch, scikit-learn job requirements
ShouldApply scores your profile against each skill at the depth level jobs actually need.
Analyze my TensorFlow, PyTorch, scikit-learn gaps →See how your depth compares to what employers actually require
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