LinkedIn Job Postings Scraper

Scrapes job listings from LinkedIn's public job search with full descriptions, hiring urgency scoring, applicant competition levels, and recruiter contact data — all without requiring a LinkedIn account.

What makes this actor different

Most LinkedIn job scrapers return basic card data: title, company, location. This actor goes deeper with a two-phase enrichment pipeline:

Feature	Basic scrapers	This actor
Job title, company, location	Yes	Yes
Full job description	No	Yes (2K-8K chars)
Applicant count & competition level	No	Yes (low/medium/high/very_high)
Seniority level	No	Yes (Associate, Mid-Senior, Director, etc.)
Employment type	No	Yes (Full-time, Contract, Internship)
Job function & industry	No	Yes
Salary / pay range	No	Yes (when company provides it)
Benefits	No	Yes (Medical, 401k, etc. when listed)
Recruiter name, title & LinkedIn profile	No	Yes (when available)
Hiring urgency scoring	No	Yes (fresh/normal/high/critical)
Applicant competition level	No	Yes (parsed from applicant counts)
Repost detection	No	Yes

How it works

Phase 1 — Search: Queries LinkedIn's public job search API to collect job cards with title, company, location, posting date, and job ID.

Phase 2 — Enrichment: For each job, fetches the full job detail page to extract the complete description, applicant count, seniority level, employment type, job function, industry, salary, benefits, and recruiter information.

Scoring: Applies hiring urgency scoring based on how long a job has been open and how many roles a company has listed. Jobs open 30+ days are flagged as critical — these companies are struggling to fill the position and are the warmest outbound leads.

No browser, no login, no cookies required. Pure API-based scraping with minimal resource usage.

Input parameters

Parameter	Type	Required	Default	Description
searchQuery	string	Yes	-	Job search keywords (e.g. "seo manager", "software engineer")
location	string	No	""	Location filter (e.g. "United States", "New York", "Remote")
maxListings	integer	No	100	Maximum number of jobs to scrape (1-1000)
datePosted	enum	No	"any"	Time filter: today, 3days, week, month, any
enrichDetails	boolean	No	true	Fetch full descriptions, applicant counts, recruiter data. Adds ~1.5s per job.
requestDelayMs	integer	No	1500	Delay between requests in milliseconds (500-10000)

Output format

Each job record contains the following fields:

{
  "job_id": "4383916783",
  "job_title": "Manager, Search Engine Marketing",
  "company_name": "Apryse",
  "company_linkedin_url": "https://www.linkedin.com/company/aprysesolutions",
  "location": "Georgia, United States",
  "date_posted": "2026-03-12",
  "days_listed": 10,
  "apply_url": "https://www.linkedin.com/jobs/view/...-4383916783",
  "description": "Full job description text with responsibilities, qualifications...",
  "seniority_level": "Not Applicable",
  "employment_type": "Full-time",
  "job_function": "Marketing and Sales",
  "industries": "Software Development",
  "applicant_count": "43 applicants",
  "applicant_competition": "medium",
  "salary_range": "$97,000.00/yr - $135,000.00/yr",
  "benefits": ["Medical insurance", "Vision insurance", "Dental insurance", "401(k)"],
  "recruiter_name": "Jane Smith",
  "recruiter_title": "Talent Acquisition Manager at Apryse",
  "recruiter_profile_url": "https://www.linkedin.com/in/jane-smith",
  "hiring_urgency": "normal",
  "is_likely_repost": false,
  "company_open_roles": 1,
  "search_query": "seo manager",
  "search_location": ""
}

Output field reference

Field	Type	Description
job_id	string	Unique LinkedIn job ID
job_title	string	Job title as posted
company_name	string	Hiring company name
company_linkedin_url	string	Company's LinkedIn page URL
location	string	Job location
date_posted	string	ISO date when the job was posted
days_listed	number	Days since posting (-1 if unknown)
apply_url	string	Direct link to the LinkedIn job posting
description	string/null	Full job description (plain text, requires enrichDetails: true)
seniority_level	string/null	Associate, Mid-Senior, Director, etc.
employment_type	string/null	Full-time, Contract, Internship, etc.
job_function	string/null	Marketing, Engineering, Sales, etc.
industries	string/null	Software Development, Hospitality, etc.
applicant_count	string/null	Raw applicant text (e.g. "43 applicants", "Over 200 applicants")
applicant_competition	string	Parsed competition level: low, medium, high, very_high, unknown
salary_range	string/null	Salary range when company provides it (e.g. "$97,000/yr - $135,000/yr")
benefits	array/null	Listed benefits (e.g. Medical insurance, 401k) when available
recruiter_name	string/null	Name of the job poster/recruiter when available
recruiter_title	string/null	Recruiter's title and company
recruiter_profile_url	string/null	Recruiter's LinkedIn profile URL
hiring_urgency	string	fresh (0-2d), normal (3-13d), high (14-29d), critical (30+d)
is_likely_repost	boolean	True if company has 4+ listings (high-volume hiring signal)
company_open_roles	number	How many jobs this company has in the current result set
search_query	string	The search query used
search_location	string	The location filter used

Hiring urgency scoring

The actor scores each listing based on how long it has been open and how aggressively the company is hiring:

Urgency	Days Listed	What it means
fresh	0-2 days	Just posted. Company is starting their search.
normal	3-13 days	Standard hiring timeline. Most jobs get filled here.
high	14-29 days	Role is getting stale. Company may be struggling to fill it.
critical	30+ days	Open over a month. High pain — warmest outbound lead.

Companies with 3+ open roles in your result set get boosted urgency. Companies with 4+ roles are flagged as is_likely_repost: true.

Applicant competition levels

Level	Applicants	What it means
low	< 25	Low competition. Early mover advantage.
medium	25-99	Moderate competition. Standard application pool.
high	100-199	High competition. Need a strong differentiator.
very_high	200+	Very competitive. Consider alternative approaches.

Use cases

• Sales & lead generation: Find companies with critical urgency hiring for roles your product/service supports. They have a proven pain point.
• Job seekers: Filter by low competition and fresh urgency to find new listings with few applicants.
• Recruiters: Identify companies struggling to fill roles (30+ days open) as potential recruitment clients.
• Market research: Track hiring trends by industry, function, seniority level, and location over time.
• Competitive intelligence: Monitor competitor hiring patterns to understand their strategic priorities.

Performance and resource usage

This actor uses no browser and no JavaScript rendering. It makes direct HTTP requests, resulting in minimal resource consumption:

Listings	Approximate runtime	Memory
50	~90 seconds	256 MB
100	~3 minutes	256 MB
500	~15 minutes	256 MB
1000	~30 minutes	256 MB

Runtime is dominated by request delays (configurable via requestDelayMs), not computation.

Tips for best results

1. Use specific search queries. "Senior SEO Manager" will return more relevant results than "marketing".
2. Combine with date filters. Use datePosted: "week" to focus on fresh listings, or datePosted: "month" to find stale listings with high urgency.
3. Set enrichDetails: true (default) to get full descriptions and applicant data. Only set to false if you just need basic listing data quickly.
4. Increase requestDelayMs to 2000-3000 if you encounter rate limiting on large scrapes.
5. Schedule recurring runs to build a longitudinal dataset and track how hiring urgency changes over time.

Limitations

• Salary data is only available when the company explicitly provides it (~10-15% of listings).
• Recruiter data is only available when the job poster opts in to the "Message the recruiter" feature (~10% of listings).
• Benefits are shown on a subset of listings.
• Results are limited to what LinkedIn's public job search returns. Some listings may only be visible to logged-in users.