LinkedIn Job Listings Scraper

Discover and extract job listings from LinkedIn using multiple search methods. Perfect for job market analysis, recruitment, and career research.

Features

• ✅ Three powerful scraping methods
• ✅ Search by keywords with advanced filters
• ✅ Scrape specific job postings
• ✅ Discover jobs from search URLs
• ✅ Get complete job details
• ✅ Export in multiple formats

Scraping Methods (Categories)

1. Collect by URL

Scrape specific job postings when you have direct job URLs.

Best for: Tracking specific positions or following up on applications

2. Discover by Keyword

Search for jobs using keywords, location, and filters.

Best for: Job market research, finding opportunities matching specific criteria

3. Discover by URL

Discover jobs from LinkedIn job search result URLs.

Best for: Scraping search results, analyzing listings in bulk

How It Works

Two-Step Process:

1. Generate Snapshot ID: Submit your search criteria or URLs
2. Fetch Data: After 30 seconds, retrieve all job listings

Input

Required Fields

• Action: Generate Snapshot ID or Fetch Data
• Category: Choose your scraping method

Category-Specific Inputs

Collect by URL

• Job URLs: Direct LinkedIn job posting URLs (one per line)

Discover by Keyword

• Keyword: Job title or search term (e.g., "software engineer")
• Location: City, state, or "Remote"
• Country: Country code (e.g., "us", "uk")
• Time Range: "past-24-hours", "past-week", "past-month"
• Job Type: "Full-time", "Part-time", "Contract", etc.
• Experience Level: "Entry level", "Mid-Senior level", "Director", etc.
• Remote Type: "On-site", "Remote", "Hybrid"
• Company: Filter by specific company name
• Location Radius: Search radius in kilometers

Discover by URL

• Job URLs: LinkedIn job search result page URLs

Input Examples

Example 1: Collect Specific Jobs

{
  "action": "generate_snap_id",
  "category": "collect_by_url",
  "urls": "https://www.linkedin.com/jobs/view/3990815942/\nhttps://www.linkedin.com/jobs/view/3990815943/"
}

Example 2: Search by Keyword

{
  "action": "generate_snap_id",
  "category": "discover_by_keyword",
  "keyword": "data scientist",
  "location": "San Francisco",
  "country": "us",
  "time_range": "past-week",
  "job_type": "Full-time",
  "remote": "Hybrid",
  "experience_level": "Mid-Senior level"
}

Example 3: From Search Results

{
  "action": "generate_snap_id",
  "category": "discover_by_url",
  "urls": "https://www.linkedin.com/jobs/search/?keywords=python%20developer&location=Remote"
}

Example 4: Fetch Data (Wait 30 seconds!)

{
  "action": "fetch_data",
  "category": "collect_by_url",
  "snap_id": "linkedin_job_listing_s_job789"
}

Data Extracted

Job Details

• Job title
• Company name and LinkedIn URL
• Job location
• Employment type (Full-time, Part-time, etc.)
• Experience level required
• Job description (full text)
• Posted date
• Number of applicants
• Direct job application URL

Additional Info

• Required skills
• Salary range (when available)
• Benefits information
• Company size
• Industries

Example Output

{
  "title": "Senior Software Engineer",
  "company": "Microsoft",
  "company_url": "https://www.linkedin.com/company/microsoft/",
  "location": "Redmond, WA",
  "employment_type": "Full-time",
  "experience_level": "Mid-Senior level",
  "description": "We are seeking an experienced software engineer to join our cloud infrastructure team...",
  "posted_date": "2024-01-15",
  "applicants": 247,
  "job_url": "https://www.linkedin.com/jobs/view/3990815942/",
  "salary_range": "$140,000 - $200,000/year",
  "workplace_type": "Hybrid",
  "skills_required": [
    "Python",
    "AWS",
    "Kubernetes",
    "Docker"
  ]
}

Step-by-Step Guide

Quick Start

1. Choose Your Method

   • Direct URLs → Use "Collect by URL"
   • Search criteria → Use "Discover by Keyword"
   • Search results → Use "Discover by URL"

2. Start Scraping

   • Select action: "Generate Snapshot ID"
   • Choose category
   • Fill in required fields
   • Run the actor
   • Copy your snapshot ID

3. Wait 30 Seconds Set a timer! This ensures all data is collected.

4. Get Your Jobs

   • Select action: "Fetch Data"
   • Select the same category
   • Enter your snapshot ID
   • Run to get results

Important Notes

⚠️ Category Must Match Use the same category when generating and fetching. If you generated with "collect_by_url", fetch with "collect_by_url".

⚠️ 30-Second Minimum Wait Fetching too early will cause errors. Wait at least 30 seconds!

⚠️ Valid URLs Required For URL-based methods, use complete LinkedIn job URLs.

Use Cases

Job Market Analysis

• Track job posting trends
• Analyze salary ranges by role
• Identify in-demand skills
• Monitor hiring activity

Recruitment & Talent

• Source candidates
• Competitive intelligence
• Job posting research
• Talent pool analysis

Career Planning

• Job search automation
• Salary research
• Skills gap analysis
• Market opportunity identification

Business Intelligence

• Competitor hiring tracking
• Market expansion research
• Industry growth indicators

Tips for Best Results

Keyword Search

• Be specific but not too narrow
• Try variations (e.g., "ML Engineer" vs "Machine Learning Engineer")
• Use location for better targeting
• Recent time ranges get more active listings

URL Collection

• Copy complete URLs from job pages
• Avoid URLs with tracking parameters
• Use search result page URLs for bulk discovery

Filters

• Combine multiple filters for precision
• Location radius helps for commutable jobs
• Experience level filters reduce noise

Common Questions

Q: How many jobs can I scrape at once? A: No hard limit, but recommend batches of 100-200 for optimal performance.

Q: Can I get historical job data? A: Only currently active postings are available.

Q: What if a job has been removed? A: You may get limited data or a note that the job is no longer available.

Q: Can I scrape jobs from all countries? A: Yes, from any LinkedIn-supported country.

Q: How accurate is the salary data? A: Extracted when available on the posting, accuracy depends on employer disclosure.

Keyword Search Filters Explained

Filter	Options	Example
Time Range	past-24-hours, past-week, past-month	past-week
Job Type	Full-time, Part-time, Contract, Temporary, Internship	Full-time
Experience Level	Internship, Entry level, Associate, Mid-Senior level, Director, Executive	Mid-Senior level
Remote	On-site, Remote, Hybrid	Remote

Data Export

Download your results in:

• JSON: Developer-friendly format
• CSV: Spreadsheet compatible
• Excel: Ready for analysis
• XML: System integration

Pricing

• Charged per job listing scraped
• All categories same price
• Snapshot IDs valid 24 hours

Troubleshooting

No results found

• Try broader keywords
• Remove location restrictions
• Expand time range
• Check spelling

Partial data

• Some employers limit visible info
• Wait longer before fetching (up to 60 seconds)

Category mismatch error

• Use same category for generate and fetch
• Double-check your input

Best Practices

1. Start Small: Test with a few jobs first
2. Use Filters: Narrow results for relevance
3. Check URLs: Verify links before bulk scraping
4. Save Snapshot IDs: Keep them for 24 hours
5. Export Regularly: Download data from dataset

Support

Having trouble?

• Review the run logs for detailed errors
• Verify your input format
• Check example inputs above
• Contact Apify support

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