Linkedin Employees Scraper

This scraper quickly collects publicly available employee information from company or school profile pages on LinkedIn. It helps users pull names, roles, locations, and profile links at scale. If you're building lead lists, researching companies, or mapping org charts, this tool makes the process fast and reliable.

     

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Introduction

This project gathers detailed employee information from LinkedIn company or institutional pages. It solves the persistent challenge of manually reviewing thousands of profiles by automating the extraction process. It’s designed for recruiters, analysts, founders, and anyone who needs structured employee data.

Why It Matters

• Helps teams build targeted outreach lists faster.
• Improves research accuracy by collecting fresh public data.
• Works across multiple companies or schools simultaneously.
• Gives users flexibility through filters like job title and country.

Features

Feature	Description
High-speed extraction	Collects up to 2,000 employee profiles in about a minute.
Multi-company support	Scrapes multiple company or school pages in one run.
Job title filtering	Lets you filter results by predefined or custom job titles.
Country targeting	Restricts results to employees from a specific country.
Alumni extraction	Retrieves profiles connected to universities or colleges.
Custom result limits	Controls how many employees are retrieved per company.

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What Data This Scraper Extracts

Field Name	Field Description
name	Publicly visible employee name.
designation	Employee job title or role.
company	Name of the company or school associated with the person.
location	Public location listed on the profile.
link	Direct URL to the employee’s LinkedIn profile.
followers	Number of profile followers if visible.
education	Public educational background.
experience	Work experience summary when available.
thumbnail	Profile image URL.
verified	Marker indicating if the profile passed validation checks.

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Example Output

[
  {
    "thumbnail": "[Image]",
    "name": "Amy ***",
    "company": "Tech***",
    "designation": "Chief ***",
    "link": "https://www.linkedin.com/in/***",
    "followers": "5***",
    "education": "Stanford University",
    "experience": "Tech***",
    "location": "San Francisco, California",
    "verified": "✅"
  },
  {
    "thumbnail": "[Image]",
    "name": "David ***",
    "company": "Data***",
    "designation": "VP ***",
    "link": "https://www.linkedin.com/in/***",
    "followers": "2***",
    "education": "MIT",
    "experience": "Data***",
    "location": "Boston, Massachusetts",
    "verified": "✅"
  }
]

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Directory Structure Tree

Linkedin Employees Scraper/
├── src/
│   ├── index.js
│   ├── helpers/
│   │   ├── parser.js
│   │   └── filters.js
│   ├── services/
│   │   ├── fetcher.js
│   │   ├── processor.js
│   │   └── exporter.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample-input.json
│   └── sample-output.json
├── package.json
├── requirements.txt
└── README.md

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Use Cases

• Recruiters use it to gather candidate lists quickly so they can focus on outreach instead of manual profile browsing.
• Sales teams use it to identify decision-makers inside target companies so they can improve lead accuracy.
• Analysts use it to study hiring patterns and organizational structures for competitive insights.
• Researchers use it to collect alumni or workforce data for academic studies.
• Founders use it to find relevant contacts for partnerships or business development.

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FAQs

Does it work for multiple companies at once? Yes, you can input several company or school URLs, and it will process all of them in a single run.

Can I limit how many employees are collected? Absolutely. Set maxResultsPerCompany to control the result count for each company.

Will filters improve result accuracy? Using job title or country filters helps narrow the dataset to only the people who match your criteria.

Does it extract alumni from universities? Yes, the scraper supports school profile URLs and can collect alumni information.

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Performance Benchmarks and Results

Primary Metric: Handles around 2,000 employee results in roughly 60 seconds under typical conditions.

Reliability Metric: Maintains a stable completion rate across both small and large company pages, even when running with multiple URLs.

Efficiency Metric: Processes simultaneous company inputs without noticeable slowdown thanks to lightweight data operations.

Quality Metric: Consistently captures complete profile fields when publicly visible, maintaining strong accuracy in role and location extraction.

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