LinkedIn Hiring Signals — Company Hiring Intelligence & Buying Intent

Turn a list of companies into hiring intelligence you can act on. For each company you get:

• its LinkedIn facts
• how fast it is hiring right now (postings in the last 7 / 30 days, relative to headcount)
• where the hiring is concentrated (department and seniority mix)
• leadership openings (new leaders bring new budgets)
• which new countries it's hiring in
• buying-intent signals mapped to what vendors sell, plus your own keyword signals

Turn on deep mode to also get the company's tech stack from its job descriptions, salary bands, applicant counts, hard-to-fill roles and compliance / IPO-readiness signals.

It reads public LinkedIn pages: no login, no cookies, no paid scraper behind it. It uses company and job data only and never reads personal profiles. Agent-callable.

Built for B2B sales and SDR teams (prospect companies showing intent), recruiters and staffing agencies (who's hiring what, and what's hard to fill), and investors/analysts (growth signals).

Tiers

• Hiring brief (default):
  • open roles found and postings in the last 7 / 30 days
  • roles per 1,000 employees, plus a hiring-momentum label and intensity score
  • department and seniority mix, leadership openings
  • top locations, countries and remote share
  • buying-intent signals and keyword signals
  • the 12 most recent roles
• Deep job-description analysis (deepAnalysis: true): reads the most recent postings in full.
  • tech stack by category (languages, cloud, data, AI, CRM/GTM, security, ERP, devtools…)
  • salary bands by department and currency
  • salary-transparency share and average applicants
  • hard-to-fill roles (open 3+ weeks with fewer than 25 applicants)
  • compliance signals (SOC 2, ISO 27001, HIPAA, PCI, GDPR, FedRAMP, SOX/IPO)

What makes it useful

Signal	Why it matters
Momentum vs company size	40 new roles at a 500-person company and at a 50,000-person company mean very different things. Postings per 1k employees normalise that. Labels: surging · active · steady · slow · hiring-pause-signals · no-open-roles-found.
Department mix	A company putting 40% of its openings into Sales is in a revenue push. Heavy Support hiring means it's scaling customer volume.
Leadership openings	A new VP/Head/Director usually arrives with a mandate, a budget, and vendor reviews.
New markets	Hiring outside the HQ country = international expansion (local vendors, localisation, legal, payroll).
Buying-intent signals	Department surges and title or description evidence are mapped to vendor categories: sales team expansion, support scaling, security investment, data platform build-out, AI initiative, recruiting ramp, finance & IPO readiness, Salesforce ecosystem, marketing build-out, engineering scale-up. Each comes with evidence and what it signals.
Your keywords	intentKeywords: ["snowflake", "soc 2"] counts open roles that mention what you sell. That is the most direct buying signal there is.
Tech stack (deep)	Job descriptions reveal the tools a team actually uses, which is technographics without guesswork.

Input

Field	Type	Required	Description
companies	array of strings	✅*	LinkedIn company URLs (exact match), company names or website domains.
intentKeywords	array of strings		Products/skills you sell into; reported per company.
datasetId	dataset	✅*	…or read companies from a lead-list dataset.
maxJobsPerCompany	integer		Open jobs read per company (default 50).
deepAnalysis	boolean		Job-description analysis add-on (default off).
jobDetailsSampled	integer		Postings read in full in deep mode (default 20).
maxCompanies	integer		Cap per run (default 20).
webhookUrl	string		POST the briefs here as JSON.

* provide companies or datasetId. For an exact match, use the LinkedIn company URL. A domain input is accepted only when the company's LinkedIn website matches it.

Example input

{ "companies": ["https://www.linkedin.com/company/stripe", "notion.com", "HubSpot"], "intentKeywords": ["salesforce", "snowflake"], "deepAnalysis": true }

Output

One brief per company. Example (real run, trimmed):

{
  "companyName": "Notion",
  "website": "https://notion.com",
  "industry": "Software Development",
  "sizeBand": "501-1,000 employees",
  "employeesOnLinkedIn": 7211,
  "openRolesFound": 50,
  "postedLast7Days": 22,
  "postedLast30Days": 48,
  "rolesPostedPer1kEmployees30d": 6.7,
  "hiringMomentum": "surging",
  "departments": [{"department": "Sales", "roles": 16, "pct": 32}, {"department": "Engineering", "roles": 15, "pct": 30}],
  "leadershipRoles": ["Head of Sales Recruiting, AMER"],
  "countries": [{"country": "United States", "roles": 37}, {"country": "Ireland", "roles": 7}, {"country": "South Korea", "roles": 4}],
  "intentSignals": [
    {"topic": "Sales team expansion", "strength": "medium", "evidence": ["16 Sales roles (32% of openings)"],
     "whatItSignals": "sales engagement, data/intent providers, sales enablement, CRM seats"}
  ],
  "topTechnologies": [{"tech": "typescript", "roles": 2}, {"tech": "react", "roles": 2}, {"tech": "aws", "roles": 2}, {"tech": "postgres", "roles": 2}],
  "salaryBands": [{"department": "Engineering", "currency": "USD", "roles": 2, "medianMin": 150000, "medianMax": 200000}],
  "avgApplicants": 139,
  "complianceSignals": ["GDPR", "SOX"],
  "summary": "Notion - 501-1,000 employees - 50 open roles found (22 in last 7d, 48 in last 30d, 6.7 per 1k employees) - top: Sales - 1 leadership opening(s) - intent: Sales team expansion, ... -> surging"
}

Use cases

• Intent-based prospecting: find accounts expanding the team your product serves, or hiring for the tool you replace.
• Account research: a one-call brief before an SDR touches an account.
• Recruiting & staffing: who's hiring what, where, and which roles are hard to fill.
• Competitive / investor research: growth vs. slowdown, new markets, new leadership, IPO-readiness hires.
• AI agents: a structured hiring brief + one-line summary per company.

Instant HTTP endpoint (Standby) - call it like a tool

Besides normal runs, this Actor answers HTTP requests directly. There's no run to start or poll; the JSON comes back in the same request, which is what an AI agent wants mid-task:

curl "https://centorprat--linkedin-hiring-signals-intelligence.apify.actor/?companies=https://www.linkedin.com/company/stripe&maxJobsPerCompany=30" -H "Authorization: Bearer <APIFY_TOKEN>"
curl -X POST "https://centorprat--linkedin-hiring-signals-intelligence.apify.actor/" -H "Authorization: Bearer <APIFY_TOKEN>" \
     -H "Content-Type: application/json" -d '{"companies": ["notion.com", "HubSpot"], "intentKeywords": ["salesforce"], "deepAnalysis": true}'

Query parameters and the POST body take the same fields as the normal input. One company returns the brief; several return {count, results}. Pricing is the same pay-per-event, charged per request; errors aren't charged.

For AI agents / MCP

https://mcp.apify.com/?tools=actors,docs,centorprat/linkedin-hiring-signals-intelligence

Loads as centorprat--linkedin-hiring-signals-intelligence. Claude Code:

claude mcp add apify -- npx -y @apify/actors-mcp-server --actors centorprat/linkedin-hiring-signals-intelligence

FAQ

Do I need a LinkedIn account or cookies? No. It reads LinkedIn's public company pages and public job search, the same pages anyone can open logged out.

Does it collect personal data? No. It reads company and job-posting data only. It never visits personal profiles and never outputs names of people.

How many jobs does it see? What LinkedIn's public job search returns for the company, worldwide, up to maxJobsPerCompany. openRolesCapped: true means there are more. Very large employers can have thousands; the recent-posting counts are then lower bounds.

How is momentum calculated? From each posting's date: new roles in the last 7 and 30 days, also relative to the company's LinkedIn employee count.

Why "intent signals"? Hiring reveals budget before anything else does: a company hiring SDRs is about to buy sales tools, and one hiring a "SOC 2 compliance lead" is about to buy GRC software. Each signal lists its evidence.

How fast? Around 10–30 s per company for the brief. Deep mode reads postings one by one and is best used in batch / webhook runs.

Cost? Pay-per-event: one event per company analysed, plus one per company when deep analysis runs. There's no underlying scraper bill.

Data & attribution

Public LinkedIn company pages and job postings. These are signals for prospecting and research, not guarantees. Counts reflect what LinkedIn's public job search shows at run time.

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