LinkedIn Hiring Signals & Job Market Analyzer

Turn public LinkedIn company pages and LinkedIn job-search URLs into a clean job dataset and auditable hiring-market insights—without supplying a LinkedIn cookie, account, proxy, or third-party API key.

Use it for recruiting research, sales timing, competitive intelligence, consulting, investment research, and job-market analysis. The Actor returns public job listings only; it does not scrape people, emails, phone numbers, or candidate profiles.

What you get

• One normalized dataset for both company and job-search inputs.
• Global deduplication by LinkedIn job ID.
• Company, role-family, seniority, employment-type, workplace, location, and posting-age distributions.
• Top hiring companies and 7-day/30-day recency counts.
• Predictable pay-per-event prices and hard owner/customer cost guards.
• Scheduling, API, export, MCP, and agent workflow compatibility through Apify.

Quick start

{
  "companyUrls": ["https://www.linkedin.com/company/apify"],
  "jobSearchUrls": ["https://www.linkedin.com/jobs/search?keywords=software%20engineer&location=United%20States"],
  "maxJobsPerInput": 25,
  "publishedWithin": "pastWeek",
  "sortBy": "recent",
  "workplaceType": "all"
}

At least one supported company URL or /jobs/search URL is required. Company filters apply only to companyUrls; filters already encoded in a job-search URL are preserved.

Output

Each default-dataset item has a stable shape: job ID and URL, title, compact company fields, normalized location, posting time and age, derived seniority, employment type, role family, Easy Apply when available, and a compact source object. Unknown facts are null or unknown; they are never guessed.

The OUTPUT key-value record contains the run status, per-input returned/unique/duplicate counts, distributions, recency metrics, top companies, warnings, endpoint prices, Monid call/cost totals, Apify event counts, and effective customer charge.

Pricing

This Actor uses Apify pay per event (PPE):

Event	Price	Trigger
apify-actor-start	$0.00005	Actor start (Apify synthetic event).
apify-default-dataset-item	$0.00001	One dataset row (Apify synthetic event).
company-profile	$0.03	A company profile is retrieved and normalized.
job-page	$0.01	A company-jobs or saved-search request succeeds.
job-result	$0.002	One unique normalized job is accepted for output.

A direct search returning 25 jobs costs about $0.06030 including synthetic micro-events. A company analysis returning 25 jobs costs about $0.09030. With an 80% creator share, current Monid costs, and expected small-run compute below $0.001, the documented company example has an estimated contribution profit near $0.059 (about 65% of customer charges), while the direct-search example is higher margin. Provider failures do not create custom success charges. If the maximum Actor charge is reached, the run preserves the successfully charged prefix and reports partial.

Partial results and safety

One failed input does not discard successful inputs. OUTPUT.status is partial when an invalid input, provider failure, or charge/cost limit affects only part of the run. The Actor inspects Monid endpoint contracts and current prices before spending, processes at most three inputs concurrently, and stops before the next paid request when the owner or customer limit cannot cover it.

Responsible use

This Actor returns public company and job-listing data. It intentionally excludes personal profile scraping and contact enrichment. Users are responsible for complying with LinkedIn terms, privacy and employment laws, and anti-discrimination rules. Derived classifications are deterministic research heuristics and must not be the sole basis for an employment decision.

This Actor is independent and is not affiliated with, authorized by, or endorsed by LinkedIn or TikHub.

Owner configuration

Customers never provide Monid credentials. The owner configures MONID_API_KEY and MONID_WORKSPACE_ID as encrypted Apify secrets, plus the three endpoint price ceilings and MONID_MAX_RUN_COST_USD. Secrets are never written to source, build arguments, logs, datasets, or OUTPUT.