# LinkedIn Job Search Scraper (`powerai/linkedin-job-search-scraper`) Actor

Extract job listings from LinkedIn with detailed metadata including job titles, company information, requirements, and direct URLs. Perfect for job market research, competitor analysis, and talent acquisition.

- **URL**: https://apify.com/powerai/linkedin-job-search-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** Jobs, Social media, Lead generation
- **Stats:** 194 total users, 2 monthly users, 89.5% runs succeeded, 8 bookmarks
- **User rating**: 1.00 out of 5 stars

## Pricing

from $4.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 💼 LinkedIn Job Search Scraper

Extract job listings from LinkedIn with detailed metadata! This powerful tool helps you gather comprehensive information about job postings, including job titles, company details, requirements, and direct URLs.

### ✨ Key Features

- 📥 Search jobs with flexible filters
- 📊 Get detailed job metadata including:
  - Job title and description
  - Company information and logo
  - Salary insights
  - Requirements and benefits
  - Workplace types
  - Company details (staff count, industries, etc.)
- 🔗 Generate direct URLs for:
  - Job postings
  - Company profiles
- 📈 Support for large result sets with automatic pagination
- 📋 Clean and structured JSON output

### 💪 Why Choose This Actor?

- **Comprehensive**: Get all job details from LinkedIn
- **Flexible**: Multiple search filters and parameters
- **Efficient**: Automatic pagination for large result sets
- **Structured**: Clean JSON output for easy integration
- **Reliable**: Stable and consistent data extraction
- **User-Friendly**: Simple input parameters

### 🎯 Perfect For

- 📊 Job Market Researchers
- 📈 HR Professionals
- 💼 Job Seekers
- 🏢 Company Analysts
- 🔍 Competitor Analysts
- 📋 Recruitment Agencies

### 📈 Use Cases

1. **Job Market Research**: Analyze job market trends
2. **Competitor Analysis**: Monitor competitor's job postings
3. **Job Discovery**: Find relevant job opportunities
4. **Salary Research**: Gather salary insights
5. **Talent Acquisition**: Source potential candidates

### 📝 Input Requirements

The actor accepts the following input parameters:

- `query` (required): The search keyword for job search
- `maxResults` (required): Maximum number of jobs to extract)
- `experience` (optional): Experience level filter (1=Internship, 2=Entry level, 3=Associate, 4=Mid senior level, 5=Director, 6=Executive)
- `jobType` (optional): Job type filter (F=Full time, P=Part time, C=Contract, T=Temporary, V=Volunteer, I=Internship, O=Other)
- `postedAgo` (optional): Time jobs were posted ago in seconds
- `workplaceType` (optional): Workplace type (1=On-Site, 2=Remote, 3=Hybrid)

#### Input Example

```json
{
  "query": "software engineer",
  "maxResults": 100,
  "experience": "2,5",
  "jobType": "F",
  "postedAgo": "3600",
  "workplaceType": "2"
}
```

#### Output Example

```json
[
      {
        "title": "Senior Software Engineer",
        "comapnyURL1": "https://www.linkedin.com/company/...",
        "comapnyURL2": "https://www.linkedin.com/company/...",
        "companyId": "123456",
        "companyUniversalName": "tech-corp",
        "companyName": "Tech Corp",
        "salaryInsights": "$120,000 - $150,000",
        "applicants": 50,
        "formattedLocation": "San Francisco, CA",
        "formattedEmploymentStatus": "Full-time",
        "formattedExperienceLevel": "Mid-Senior level",
        "formattedIndustries": "Software Development",
        "jobDescription": "We are looking for a Senior Software Engineer...",
        "inferredBenefits": "Health insurance, 401(k), Remote work",
        "jobFunctions": "Engineering, Information Technology",
        "workplaceTypes": ["remote"],
        "company_data": {
          "name": "Tech Corp",
          "logo": "https://...",
          "backgroundCoverImage": "https://...",
          "description": "Leading technology company...",
          "staffCount": 1000,
          "staffCountRange": {
            "staffCountRangeStart": 500,
            "staffCountRangeEnd": 2000
          },
          "universalName": "tech-corp",
          "url": "https://www.linkedin.com/company/...",
          "industries": ["Software Development", "Technology"],
          "specialities": ["Cloud Computing", "AI"]
        },
        "companyApplyUrl": "https://www.linkedin.com/jobs/view/...",
        "jobPostingUrl": "https://www.linkedin.com/jobs/view/...",
        "listedAt": "2024-03-15T10:00:00Z",
        "scrapedAt": "2024-03-15T11:00:00Z"
      },
      ...
]

```

# Actor input Schema

## `query` (type: `string`):

The search keyword for job search

## `maxResults` (type: `integer`):

Maximum number of jobs to extract

## `experience` (type: `string`):

Experience level required for the job (1=Internship, 2=Entry level, 3=Associate, 4=Mid senior level, 5=Director, 6=Executive). Multiple values can be specified with commas (e.g., '2,5')

## `jobType` (type: `string`):

Job type filter (F=Full time, P=Part time, C=Contract, T=Temporary, V=Volunteer, I=Internship, O=Other)

## `postedAgo` (type: `string`):

Time jobs were posted ago in seconds (e.g., 3600 for past 1 hour)

## `workplaceType` (type: `string`):

Workplace type (1=On-Site, 2=Remote, 3=Hybrid)

## Actor input object example

```json
{
  "query": "software engineer",
  "maxResults": 25,
  "experience": "",
  "jobType": "",
  "postedAgo": "",
  "workplaceType": ""
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "software engineer"
};

// Run the Actor and wait for it to finish
const run = await client.actor("powerai/linkedin-job-search-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "software engineer" }

# Run the Actor and wait for it to finish
run = client.actor("powerai/linkedin-job-search-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "software engineer"
}' |
apify call powerai/linkedin-job-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,powerai/linkedin-job-search-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/lRN6qfGqVrTHNNfU0/builds/j66le0WcJ4nzsGZvX/openapi.json