Skill Demand Index
Based on 2 scored job postings out of 2,412 total. Depth levels reflect actual proficiency tiers, not just keyword presence.
0.1%
Demand Rate
L5
Median Depth
0%
Gap Rate
2
Jobs Analyzed
Advanced
Most employers want Data-Driven Recommendations at lead-level proficiency, not surface awareness.
Overview
Market context for Data-Driven Recommendations in the current job market
Data-Driven Recommendations is required in 0.1% of scored job postings on ShouldApply, making it a growing skill in the current job market. Employers looking for Data-Driven Recommendations typically want candidates who can demonstrate real proficiency, not just surface awareness.
What the data shows for Data-Driven Recommendations:
What L5 means in practice:
L4 (Advanced) means solving hard problems, optimizing workflows, and mentoring others. Employers want someone who can be the go-to person for Data-Driven Recommendations on their team.
This means employers aren't looking for someone who has used Data-Driven Recommendations 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 Data-Driven Recommendations proficiency. To stand out, aim for L4-L5 depth with concrete evidence.
Which roles need Data-Driven Recommendations most:
Software Engineering positions drive 100% of demand. Skills commonly paired with Data-Driven Recommendations include Bachelor's Degree and B2B SaaS Experience.
Depth Level Distribution
How candidates match Data-Driven Recommendations requirements across 2 scored evaluations
Average depth: L4.5·Median depth: L4.5
Salary Correlation
How Data-Driven Recommendations affects compensation based on postings with disclosed salary data
Without Data-Driven Recommendations
$137K
Median $130K
450 jobs
Skill Demand Insight
“Data-Driven Recommendations appears in 0.1% of all scored jobs.”
From 2 scored job postings
Skill Pairings
Other skills that frequently appear alongside Data-Driven Recommendations
100%
co-occurrence
100%
co-occurrence
100%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
50%
co-occurrence
Role Breakdown
Job categories most likely to require Data-Driven Recommendations
Gap Analysis
How often Data-Driven Recommendations is identified as a skill gap (L0–L1) in scored applications
Very low gap rate — candidates generally have this skill
When Data-Driven Recommendations appears in a job's requirements, 0% of scored applicants received an L0 or L1 (missing or minimal).
Yes. Data-Driven Recommendations 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.
The median required depth is L5. Most employers want advanced proficiency — candidates who can lead projects and optimize processes.
Salary data for Data-Driven Recommendations is still accumulating.
The most common pairings are Bachelor's Degree, B2B SaaS Experience, People Management, Marketing Analytics, Data Visualization Tools (Tableau). Strengthening these alongside Data-Driven Recommendations improves your fit across more positions.
Top roles: Software Engineering. Software Engineering positions have the highest demand at 100% of all Data-Driven Recommendations 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 Data-Driven Recommendations job requirements
ShouldApply scores your profile against each skill at the depth level jobs actually need.
Analyze my Data-Driven Recommendations gaps →See how your depth compares to what employers actually require
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