LinkedIn Job Scraper for Apify

A LinkedIn job scraper this scraper extracts comprehensive job listings from LinkedIn with advanced data processing and cleaning capabilities.

🚀 Features

• LinkedIn Integration: Direct scraping from LinkedIn job listings
• Smart Data Processing: Automatic extraction of skills, experience requirements, and salary information
• Flexible Configuration: Customizable search parameters and filters
• Data Enhancement: Cleans and formats job descriptions, URLs, and metadata
• Apify Optimized: Built specifically for deployment on the Apify platform
• Error Handling: Robust error handling with detailed logging

⚙️ Configuration

The scraper accepts the following input parameters:

Required Parameters

• search_term (string): Job title or keywords to search for

  • Default: "python developer"
  • Examples: "data scientist", "frontend developer", "product manager"

• location (string): Geographic location for job search

  • Default: "United States"
  • Examples: "New York, NY", "Remote", "London, UK"

Optional Parameters

• results_wanted (integer): Number of job results to fetch

  • Default: 50
  • Range: 1-1000

• hours_old (integer): Maximum age of job postings in hours

  • Default: 168 (7 days)
  • Examples: 24 (1 day), 72 (3 days)

• job_type (string): Type of employment

  • Options: "fulltime", "parttime", "contract", "internship"

• is_remote (boolean): Filter for remote jobs only

  • Default: false

• easy_apply (boolean): Filter for jobs with easy apply option

  • Default: false

• distance (integer): Search radius in miles from location

  • Default: 25

📊 Output Data

Each job record includes the following fields:

Basic Information

• company: Company name
• title: Job title
• location: Job location
• date_posted: When the job was posted
• site: Source site (LinkedIn)

URLs and Links

• job_url: Direct link to job posting
• job_url_direct: Direct application URL
• company_url: Company profile URL
• company_logo: Company logo URL

Job Details

• description: Cleaned job description
• salary: Extracted salary information
• job_level: Seniority level
• job_function: Job category/function
• work_type: Employment type

Enhanced Data

• skills: Extracted required skills
• experience_range: Required experience level
• id: Unique job identifier

🔧 Usage Examples

Basic Usage (Apify Input)

{
  "search_term": "data scientist",
  "location": "San Francisco, CA",
  "results_wanted": 100
}

🧠 Smart Features

Skill Extraction

Automatically identifies and extracts relevant skills from job descriptions including:

• Programming languages (Python, Java, JavaScript, etc.)
• Frameworks (React, Django, Flask, etc.)
• Cloud platforms (AWS, Azure, GCP)
• Databases (SQL, MongoDB, PostgreSQL)
• Tools and methodologies (Docker, Kubernetes, Agile, etc.)

Experience Level Detection

Intelligently categorizes experience requirements:

• Entry level (0-1 years)
• Specific ranges (2-5 years)
• Senior level (5+ years)
• Minimum requirements

Salary Information

Extracts salary data from multiple sources:

• Structured salary fields
• Job description text parsing
• Multiple currency formats (USD, INR, etc.)
• Various formats (annual, hourly, LPA, etc.)

Data Cleaning

• Removes markdown formatting
• Fixes URL escaping issues
• Standardizes text formatting
• Handles missing data gracefully

📈 Performance Tips

1. Optimize Results: Start with smaller results_wanted values for testing
2. Filter Early: Use hours_old to focus on recent postings
3. Location Specificity: More specific locations yield better results
4. Batch Processing: For large datasets, consider multiple smaller runs

🐛 Troubleshooting

Common Issues

1. No Results Found

   • Check if search terms are too specific
   • Verify location spelling
   • Increase hours_old parameter

2. Rate Limiting

   • Reduce results_wanted
   • Add delays between runs
   • Check Apify platform limits

3. Data Quality Issues

   • Review job descriptions for parsing errors
   • Check URL formatting
   • Validate extracted skills

📄 License

This project is licensed under the MIT License.

Note: This scraper is designed for educational and research purposes. Please ensure compliance with LinkedIn's Terms of Service and applicable laws when using this tool.