LinkedIn Job Skills Demand Scraper

Scrape and measure how often selected technologies appear in public LinkedIn job titles and descriptions. Get one auditable aggregate per skill with matching-job counts, share of searched jobs, top companies, top locations, and sample source postings.

Use it for workforce planning, curriculum design, developer-tool market research, technology adoption signals, and recruiting strategy without a LinkedIn login or private-profile access.

Open the five-skill backend-demand Task to inspect the bounded US analysis before running. The maximum Actor charge is $0.04 for five completed skill aggregates; inspected jobs, failed fetches, and RUN_SUMMARY diagnostics are free.

How the analysis works

The Actor searches public jobs, fetches descriptions, and matches each requested skill case-insensitively with alphanumeric boundaries. It does not use an opaque AI model or infer synonyms. For example, AWS counts explicit AWS mentions; related cloud terms are not silently added.

Choose this Actor when

Use this Actor when you need one auditable aggregate per exact skill rather than raw job rows. For broad job discovery use LinkedIn Jobs Search Scraper. For complete records from known IDs or URLs use LinkedIn Job Details Scraper.

Example input

{
  "queries": ["software engineer"],
  "locations": ["United States"],
  "datePosted": "r604800",
  "skills": ["Python", "Java", "SQL", "AWS", "Kubernetes"],
  "maxResultsPerQuery": 50
}

First run checklist

1. Start with one query, one location, 25 jobs, and no more than five skills.
2. Verify matchingJobs, searchedJobs, shareOfJobs, and sampleJobUrls for every skill.
3. Check RUN_SUMMARY for jobs scanned, skill aggregates saved, and billable rows.
4. Reuse identical inputs in scheduled Tasks when comparing changes over time.

Output fields

Each requested skill produces one row:

• skill, matchingJobs, searchedJobs, shareOfJobs
• topCompanies as company and matching-job counts
• topLocations as location and matching-job counts
• sampleTitles, sampleJobUrls, scrapedAt

shareOfJobs is matchingJobs / searchedJobs for this bounded run. It is not a claim about the entire labor market. Use consistent queries, locations, recency, and result limits when comparing scheduled runs.

RUN_SUMMARY is stored outside the Dataset and is never billed. It separates inspected public jobs from saved skill-aggregate rows.

Practical workflows

• Compare cloud, data, AI, or backend skills for curriculum planning
• Monitor demand for a product's integrations or technology category
• Track which employers and locations mention a skill most often
• Create weekly time series by scheduling the same Apify Task
• Feed aggregates and source URLs into BI, RAG, or research workflows

Call it from ChatGPT, Claude, n8n, Make, Zapier, a notebook, a data warehouse, or the Neuton Actors MCP Server.

Pricing

Launch price: $8.00 per 1,000 returned skill aggregates ($0.008 each), or $0.80 for 100. Five requested skills normally produce five result rows, or about $0.04 in Actor charges. The price is attached to the useful aggregate output rather than every underlying job inspected. This is a margin-first price.

Skills demand SEO keywords

LinkedIn skills demand analyzer, technology job trends, workforce planning data, curriculum demand research, developer skills API, labor market intelligence.

LinkedIn jobs workflow family

• LinkedIn Remote Jobs Scraper & Intelligence for strict remote-role filtering
• LinkedIn Salary Jobs Scraper for compensation benchmarking
• LinkedIn Easy Apply Jobs Scraper for in-platform application paths
• LinkedIn Company Hiring Signals Scraper for account-level hiring intent

Responsible use

This Actor processes public job-posting information. Samples and keyword counts can be incomplete or biased by the chosen search. Verify source rows and methodology before consequential workforce or education decisions. Do not use it for spam, unlawful discrimination, private-profile collection, access-control bypass, or excessive requests. This Actor is not affiliated with or endorsed by LinkedIn.