LinkedIn Job Data Scraper

Tap into the world's largest professional talent ecosystem.

LinkedIn is more than a job board—it's the professional identity layer of the internet with 1 billion+ members across 200+ countries. Unlike traditional job sites, LinkedIn jobs come with rich company insights, employee growth data, and applicant analytics. This scraper extracts premium job intelligence including applicant counts, hiring team info, company growth metrics, and skill requirements that only LinkedIn provides.

🌟 Why choose this Actor?

Built for LinkedIn's unique professional data ecosystem, this Actor unlocks insights no other job platform can offer.

Feature	LinkedIn Job Data Scraper	Bright Data	Zyte
Pricing Model	✅ $0.003/job	❌ $500+/month	❌ Enterprise only
No Commitment	✅ Pay-per-result	❌ Monthly contract	❌ Annual contract
Unified Schema	✅ Normalized output	✅ Yes	✅ Yes
Setup Complexity	✅ No-code, 1-click	⚠️ Technical setup	❌ Complex setup
LinkedIn Focus	✅ Specialized	⚠️ Generic	⚠️ Generic

🏆 Key Features

📊 LinkedIn-Exclusive Data Extraction

• 👥 Applicant Intelligence: Track real-time applicant counts—spot high-competition roles vs. hidden gems with fewer applicants.
• 📈 Company Growth Signals: Access employee count trends, recent hires, and company expansion data unique to LinkedIn.
• 🎯 Skill-Based Matching: Extract structured skill requirements that power LinkedIn's job-candidate matching algorithm.
• 👔 Hiring Team Visibility: See who posted the job—recruiters, hiring managers, or talent acquisition teams.
• 🏢 Rich Company Profiles: Leverage LinkedIn's company pages for industry, size, specialties, and verified company data.
• ⚡ Easy Apply Detection: Identify jobs with LinkedIn's streamlined application process for faster candidate pipelines.
• 🌍 200+ Countries: Access LinkedIn's truly global professional network across every major market.

🎯 Use Cases

🔎 Talent Intelligence & Recruiting

• Competitive Hiring Analysis: Monitor which roles competitors post and their applicant traction—data only LinkedIn reveals.
• Passive Candidate Sourcing: Build talent pools by analyzing job requirements and skill demands in your industry.
• Recruiter Workload Optimization: Identify jobs with low applicant counts for higher placement success rates.
• Employer Branding Research: Study how top companies position their job postings and employer value propositions.

📈 Labor Market Analytics

• Skill Demand Forecasting: Track emerging skills and certifications trending across LinkedIn job postings.
• Company Growth Radar: Correlate job posting volume with company expansion signals and funding rounds.
• Remote Work Trends: Analyze the shift to remote/hybrid roles across industries and geographies.
• Salary Benchmarking: Compare compensation data across roles, seniority levels, and locations.

🏢 Strategic Workforce Planning

• Talent Market Mapping: Identify talent hotspots and emerging tech hubs based on job concentration.
• Competitor Org Structure Analysis: Reverse-engineer competitor team structures from their job postings.
• Skills Gap Analysis: Compare your workforce skills against market demand signals from LinkedIn jobs.
• Headcount Planning: Use hiring trends to forecast industry growth and plan your own expansion.

🤖 AI & ML Applications

• Job-Candidate Matching Models: Train ML models on LinkedIn's structured skill and experience requirements.
• Career Path Prediction: Analyze job progressions and seniority patterns for career coaching AI.
• Resume Optimization Engines: Use job requirement data to power ATS-friendly resume builders.
• Conversational Career Assistants: Feed real-time job data to chatbots for personalized career advice.

💰 Pricing

Resource	Cost	Description
Actor Usage	$0.00001	Charged for Actor runtime. Cost depends on resource consumption during execution.
Job Details	$0.00252	Charged for each job posting scraped. Includes complete metadata such as applicant count, skills, company data, and more. Flat fee per job.

Example Cost Calculation:

• Scraping "Product Manager" + "Data Scientist" in San Francisco Bay Area
• 2 keywords × 150 jobs = 300 results → 300 × $0.00252 = $0.76 total

🧜 How it Works

💻 Input Parameters

{
  "search_terms": ["Product Manager", "Software Engineer"],
  "country": "United States",
  "location": "San Francisco Bay Area",
  "posted_since": "1 week",
  "max_results": 200
}

Parameter	Type	Required	Description	Example
search_terms	string[]	✅	Keywords to search: job titles, skills, or company names	["Data Analyst", "Business Intelligence"]
country	string	✅	Target country for job search (200+ countries on LinkedIn)	United States
location	string	❌	City, metro area, or region (optional)	New York City Metropolitan Area
posted_since	string	✅	Filter jobs posted within this period ("24 hours", "1 week", "1 month")	1 week
max_results	integer	✅	Number of jobs to fetch per keyword (min: 10)	500

📤 Output Structure

{
  "processor": "https://apify.com/nextapi/linkedin-job-data-scraper",
  "processed_at": "2025-11-26T14:30:00+00:00",
  "platform": "LinkedIn",
  "platform_url": "https://www.linkedin.com/jobs/view/3847291056",
  "official_url": "https://careers.google.com/jobs/results/senior-product-manager",
  "title": "Senior Product Manager, Cloud AI",
  "posted_date": "2025-11-22T00:00:00+00:00",
  "location": "Mountain View, CA",
  "is_remote": false,
  "description": "Join Google Cloud's AI team to shape the future of enterprise AI products!\n\n## What you'll do\n- Define product roadmap for Cloud AI services\n- Partner with engineering to deliver world-class ML infrastructure\n- Drive go-to-market strategy with cross-functional teams\n- Analyze market trends and competitive landscape",
  "job_type": "full-time",
  "job_level": "senior",
  "job_function": "Product Management",
  "listing_type": "promoted",
  "emails": null,
  "skills": "Product Strategy, Machine Learning, Cloud Computing, Agile, SQL, Stakeholder Management",
  "work_from_home": "hybrid",
  "vacancy_count": 3,
  "experience_range": "5-8 years",
  "salary_period": "yearly",
  "salary_minimum": 180000,
  "salary_maximum": 260000,
  "salary_currency": "USD",
  "company_name": "Google",
  "company_industry": "Technology, Information and Internet",
  "company_url": "https://www.linkedin.com/company/google",
  "company_website": "https://google.com",
  "company_logo": "https://media.licdn.com/dms/image/C4D0BAQHiNSL4Or29cg/company-logo_200_200/google-logo.png",
  "company_addresses": "1600 Amphitheatre Parkway, Mountain View, CA 94043",
  "company_revenue": "$280B+",
  "company_description": "A technology company that specializes in Internet-related services and products, including online advertising, search engine, cloud computing, and AI.",
  "company_rating": 4.4,
  "employee_count": "100001+",
  "review_count": 45000
}

📊 Output Fields Description

Job Information

Field	Type	Description
processor	string	URL of the Apify actor that processed this data
processed_at	string	ISO 8601 timestamp when the data was processed
platform	string	Source platform (LinkedIn)
platform_url	string	Direct job URL on LinkedIn
official_url	string	Company's careers page link (when available)
title	string	Job position title
posted_date	string	Date when job was posted
location	string	Job location (city, metro area, or "Remote")
is_remote	boolean	Whether the job allows remote work
description	string	Full job description in markdown format
job_type	string	Employment type (full-time, part-time, contract, internship)
job_level	string	Seniority level (entry, associate, mid-senior, director, executive)
job_function	string	LinkedIn job function category
listing_type	string	Listing visibility (standard, promoted, featured)
emails	string	Contact emails found in job posting
skills	string	Required skills extracted from LinkedIn's skill tags
work_from_home	string	Work model (remote, hybrid, on-site)
vacancy_count	integer	Number of open positions for this role
experience_range	string	Required years of experience

Salary Information

Field	Type	Description
salary_period	string	Payment period (yearly, monthly, hourly)
salary_minimum	number	Minimum salary amount
salary_maximum	number	Maximum salary amount
salary_currency	string	Currency code (USD, EUR, GBP, etc.)

Company Information (LinkedIn-Enriched)

Field	Type	Description
company_name	string	Verified company name from LinkedIn
company_industry	string	LinkedIn industry classification
company_url	string	LinkedIn company page URL
company_website	string	Official company website
company_logo	string	Company logo from LinkedIn CDN
company_addresses	string	Headquarters and office locations
company_revenue	string	Annual revenue range
company_description	string	Company "About" section from LinkedIn
company_rating	number	Company rating score (out of 5)
employee_count	string	LinkedIn employee count range
review_count	integer	Number of company reviews

🔌 Integrations

Seamlessly connect this actor to your existing pipelines via the Apify API.

🆔 Actor ID:

dJWj757pVx5untEuq

Python Client

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("nextapi/linkedin-job-data-scraper").call(run_input={
    "max_results": 100,
    "posted_since": "1 week",
    "country": "United States",
    "location": "Seattle",
    "search_terms": ["Software Engineer", "Machine Learning Engineer"]
})

for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{job['title']} at {job['company_name']} | {job.get('employee_count', 'N/A')} employees")

Node.js Client

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });
const run = await client.actor("nextapi/linkedin-job-data-scraper").call({
  max_results: 100,
  posted_since: "2 weeks",
  country: "United States",
  location: "Austin, Texas",
  search_terms: ["DevOps Engineer", "Site Reliability Engineer"],
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((job) =>
  console.log(`${job.title} at ${job.company_name} - ${job.work_from_home}`)
);

🦜 LangChain

Use this actor as a document loader in LangChain to power your RAG pipelines with LinkedIn's professional job data for career coaching AI and recruitment chatbots.

🏗️ Metadata for Developers (JSON-LD)

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "LinkedIn Job Data Scraper",
  "applicationCategory": "DeveloperApplication",
  "operatingSystem": "Cloud",
  "offers": {
    "@type": "Offer",
    "price": "0.00",
    "priceCurrency": "USD"
  },
  "description": "LinkedIn Job Scraper API - Extract professional job listings from the world's largest career network. Get job titles, salaries, skills, applicant insights, company growth data & hiring team info. Covers 200+ countries with real-time data. Built for recruiters, HR tech, and talent intelligence platforms."
}

🚀 Performance Tips

Optimize your runs for speed, cost, and reliability with these best practices:

💰 Cost Optimization

• Start Small: Test with max_results: 10 and a single search term before scaling up.
• Monitor Costs: Check the "Usage" tab in Apify Console for real-time cost tracking. Each job costs $0.00252.
• Precise Keywords: Use specific job titles (e.g., "Senior Frontend Engineer" vs. "Developer") to get more relevant results.

⚡ Speed Optimization

• Fewer Keywords: Each search term creates a separate search. Combine related roles into one keyword.
• Metro Area Focus: LinkedIn uses metro areas—specify these for better location targeting (e.g., "San Francisco Bay Area").
• Recent Posts: Use "24 hours" or "1 week" for faster results and fresher job data.

🛡️ Reliability Best Practices

• Valid Country Names: Use full country names exactly as LinkedIn displays them (e.g., "United States", not "USA" or "US").
• Monitor Progress: Use Apify Console's live log to track scraping progress in real-time.

📊 Data Quality Tips

• Salary Transparency: LinkedIn salary data comes from employer disclosures and member-reported data. Filter by salary_minimum to focus on jobs with compensation info.
• Fresh Data: LinkedIn job postings are highly dynamic. Schedule daily or weekly runs for time-sensitive recruiting.
• Remote Filter: Use is_remote: true or check work_from_home field to find remote-friendly positions.
• Company Verification: LinkedIn verifies company pages—company_url links to authentic company profiles.

❓ FAQ

How to export job listings to Excel?

After the run completes, go to the Output tab in the Apify Console. Click the Export button and select Excel format. You'll get a structured spreadsheet with all LinkedIn job data ready for analysis.

How do I find remote-only jobs?

Currently, the actor fetches all matching jobs. Filter results by checking the is_remote field (boolean) or work_from_home field for "remote" or "hybrid" values.

Why are some salary fields empty?

LinkedIn salary data depends on employer disclosure and is more common for US jobs due to pay transparency laws. Jobs in states like California, Colorado, and New York more frequently include salary ranges.

How long does a typical scrape take?

Runtime depends on the number of search terms and max_results setting. A typical run with 2-3 keywords and 100 results completes in 1-3 minutes.

Why do some job titles not match my search keywords exactly?

LinkedIn's search algorithm prioritizes relevance over exact matching. Results may include:

• Related job titles and synonyms (e.g., "Product Manager" may return "Program Manager" roles)
• Jobs matching your skills or industry context
• Roles from companies you've shown interest in
• Location-adjusted relevance based on market data

This mirrors the actual LinkedIn job search experience.

How is LinkedIn data different from other job boards?

LinkedIn provides unique professional context:

• Company verification through LinkedIn company pages
• Employee count and growth trends not available elsewhere
• Skills taxonomy aligned with LinkedIn's professional graph
• Seniority level standardization across all jobs
• Industry classification based on LinkedIn's company data

⚖️ Legal & Compliance

This actor scrapes publicly available job postings only. It does not log in, access private member data, or collect personal information of job seekers or recruiters. You are responsible for adhering to LinkedIn's Terms of Service and applicable privacy laws (GDPR/CCPA).

🏷️ LinkedIn Job Data Scraper

🔥 Search Terms: linkedin scraper, linkedin jobs api, linkedin job listings, linkedin salary data, linkedin data extraction, linkedin job search, linkedin automation, linkedin job aggregator, linkedin job parser, linkedin career data, linkedin talent intelligence, linkedin recruiting api, linkedin hiring data, linkedin company insights, linkedin employee data, linkedin skills extraction, linkedin job feed, professional network scraper, b2b job data, enterprise recruiting data

💼 Use Cases: talent-intelligence recruiting-automation labor-market-analytics competitive-hiring-analysis workforce-planning career-platform hr-tech talent-acquisition skills-gap-analysis salary-benchmarking company-research headcount-planning job-matching-ai recruitment-analytics

🤝 Support & Community

• 📧 Support: Contact Us | 💬 Community: Telegram Group

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