LinkedIn Company Hiring Signals Scraper

Scrape public LinkedIn job searches into company-level hiring-intent rows for account-based sales, recruiting intelligence, competitor tracking, and market research. Instead of exporting one row per job, this Actor groups the current search results by employer and explains each score with jobs, locations, role families, and source URLs.

Open the bounded AI-team expansion Task to inspect an editable two-query search capped at ten jobs per query. Only completed company aggregates are billed at $0.008 each; inspected jobs, diagnostics, and companies below the evidence threshold are free.

What the hiring signal means

For each company meeting minimumCompanyJobs, the Actor calculates a transparent 0-100 score from:

• the number of open jobs found in this run
• the number of listings with public posting dates
• the number of distinct hiring locations

The result is labelled moderate, good, or strong. It is a rule-based signal from the bounded search run, not an AI prediction of company revenue, funding, or purchase intent.

Choose this Actor when

Use this Actor when you need one auditable company aggregate instead of one row per job. 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": ["sales", "engineering"],
  "locations": ["United States"],
  "datePosted": "r604800",
  "maxResultsPerQuery": 50,
  "minimumCompanyJobs": 2
}

First run checklist

1. Start with one query, one location, 25 jobs, and minimumCompanyJobs set to 2.
2. Verify openJobsInRun, roleFamilyCounts, sampleJobUrls, and the score explanation.
3. Check RUN_SUMMARY for jobs scanned, company rows saved, and billable rows.
4. Expand or schedule the Task only after the bounded aggregate fits your workflow.

Output fields

Each company-level row includes:

• company, companyUrl, openJobsInRun
• hiringSignalScore, hiringSignalLabel
• locations, roleFamilyCounts, searchQueries
• sampleTitles, sampleJobUrls, scrapedAt

roleFamilyCounts groups titles into engineering, data, sales, marketing, product, operations, finance, people, or other. Sample titles and URLs make every aggregate auditable.

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

Sales and research workflows

• Monitor named role families for account expansion signals
• Rank companies hiring sales, engineering, data, or operations teams
• Track geographic expansion through newly observed locations
• Feed a CRM or warehouse while retaining public source evidence
• Schedule recurring Tasks and compare openJobsInRun over time

Send the rows to ChatGPT, Claude, Clay, n8n, Make, Zapier, a BI tool, or the Neuton Actors MCP Server.

Pricing

Launch price: $8.00 per 1,000 returned company hiring signals ($0.008 each). A 100-company output costs about $0.80 in Actor charges. Underlying job candidates that do not produce a qualifying company aggregate are not returned as company-result rows. This is a margin-first price.

Hiring signals SEO keywords

LinkedIn hiring signals, company hiring intent, sales trigger data, account-based sales data, LinkedIn jobs intelligence, company growth signals, recruiting market research.

LinkedIn jobs workflow family

• LinkedIn Remote Jobs Scraper & Intelligence for remote hiring feeds
• LinkedIn Salary Jobs Scraper for compensation research
• LinkedIn Easy Apply Jobs Scraper for application-path monitoring
• LinkedIn Job Skills Demand Scraper for technology demand by skill

Responsible use

This Actor processes public job-posting information. Hiring activity is only one incomplete business signal; verify the source rows before consequential decisions. Do not use the output for spam, unlawful discrimination, private-profile collection, access-control bypass, or excessive requests. This Actor is not affiliated with or endorsed by LinkedIn.