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 json { "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 json { "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 json { "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!) json { "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 json { "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 --- Find your next opportunity or insight! 💼