Linkedin Job Scraper πΌ
Pricing
$3.00 / 1,000 results
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Linkedin Job Scraper πΌ
Collect LinkedIn job listings effortlessly π Extract structured job data for recruitment, market research, and career analysis β fast, reliable, and scalable β‘
Pricing
$3.00 / 1,000 results
Rating
0.0
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Developer

WebScrap
Maintained by Community
Actor stats
3
Bookmarked
31
Total users
10
Monthly active users
3 days ago
Last modified
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LinkedIn Job Scraper - Pay Per Event
A professional job scraping service that extracts job listings from LinkedIn using a pay-per-event pricing model. You only pay for the results you receive.
π Pay-Per-Event Pricing
This Actor uses Pay-Per-Event (PPE) pricing with the following events:
Events Charged:
- (Synthetic Event) - $0.003 per item
- Charged for each job result delivered to your dataset
- Includes both successful job results and error responses
- No manual charging needed - automatically triggered by data delivery
Cost Examples:
- 20 jobs found: ~$0.02005 (1x start + 20x results)
- 100 jobs found: ~$0.10005 (1x start + 100x results)
- No jobs found: ~$0.00105 (1x start + 1x error response)
π What You Get
Each job result includes:
- Company name and profile
- Job title and description
- Location and remote work status
- Job type (Full-time, Part-time, Contract, Internship)
- Experience level requirements
- Application URL
- Posting date
- Categorized job type (Frontend, Backend, Data Science, etc.)
π§ Configuration
Required Parameters:
- Search Term: Keywords to search for (e.g., "software engineer")
- Location: Geographic location (e.g., "San Francisco, CA")
Optional Parameters:
- Results Per Site: Number of jobs to fetch (1-500, default: 20)
- Maximum Job Age: Only show jobs posted within X hours (default: 72)
- Distance: Maximum distance from location in miles (default: 50)
- Job Type: Filter by employment type (fulltime, parttime, internship, contract)
- Remote Only: Only show remote positions (default: false)
- Result Offset: Skip first N results for pagination (default: 0)
- Proxies: Optional proxy list for enhanced reliability
π‘ Best Practices
- Spending Control: Set spending limits in the Apify Console to control costs
- Result Optimization: Use specific search terms to get more relevant results
- Location Targeting: Be specific with locations for better job matches
- Type Filtering: Use job_type parameter to filter by employment type
π― Revenue Model
This Actor generates revenue through:
- Transparent per-result pricing
- No hidden subscription fees
- Pay only for successful data delivery
- Automatic charging handled by Apify platform
π οΈ Technical Implementation
- Uses JobSpy library for reliable LinkedIn scraping
- Implements Apify's synthetic charging events
- Includes automatic retry logic and proxy rotation
- Provides structured data output with consistent schema
- Handles rate limiting and anti-bot protection
π Scaling
- Handles 1-500 results per run
- Supports proxy rotation for higher volume
- Implements batched data delivery
- Respects user spending limits automatically
Start scraping jobs now and pay only for what you get!