# LinkedIn Jobs Scraper Pro (`data_dino/linkedin-jobs-scraper-pro`) Actor

Extract 1,000 LinkedIn job listings in ~5 minutes. No login, no cookies, no account risk — just fast, reliable job data from 45+ countries.

- **URL**: https://apify.com/data\_dino/linkedin-jobs-scraper-pro.md
- **Developed by:** [Data Dino](https://apify.com/data_dino) (community)
- **Categories:** Lead generation, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.25 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## 🔥 LinkedIn Jobs Scraper

Extract 1,000 LinkedIn job listings in ~5 minutes. No login, no cookies, no account risk — just fast, reliable job data from 45+ countries.

***

### What Makes It Different

- **Zero-cookie, zero-risk.** Most LinkedIn scrapers require cookies or login — putting your account at risk. This one runs entirely on residential proxies with no account needed. Your LinkedIn profile stays safe.
- **Adaptive throughput.** Automatically scales scraper concurrency based on available memory. More RAM = more simultaneous scrapers = faster results. At 4 GB, you get ~500 results/minute.
- **Full job descriptions + direct apply URLs.** Fetches the complete job listing (not just a preview snippet) along with the employer's own careers page link. No other scraper in this price range gives you both.

***

### Sample Output

```json
[
  {
    "title": "Software Engineer, New Grad (AI)",
    "company": "Notion",
    "location": "San Francisco, CA",
    "job_url": "https://www.linkedin.com/jobs/view/4407498584",
    "id": "li-4407498584",
    "date_posted": "2026-06-09",
    "description": "**About The Role**\nAs an engineer at Notion, you'll help shape...",
    "site": "linkedin",
    "job_type": "fulltime",
    "min_amount": null,
    "max_amount": null,
    "currency": null,
    "is_remote": false,
    "job_level": "entry level",
    "job_function": "Engineering and Information Technology",
    "listing_type": null,
    "emails": null,
    "company_industry": "Software Development",
    "company_url": "https://www.linkedin.com/company/notionhq",
    "company_logo": "https://media.licdn.com/dms/image/v2/D4E0BAQGwvcv_1tHZ4w/company-logo_100_100/...",
  }
]
```

***

### Input

| Field | Type | Required | Description | Default |
|---|---|---|---|---|
| `keywords` | string\[] | ✅ | Job titles or keywords to search. Each keyword runs as an independent scrape (e.g. `["software engineer", "data analyst"]`). LinkedIn boolean operators are supported. | — |
| `location` | string | — | City, state, or region. Fold country into your location string for best results (e.g. `"London, United Kingdom"`, `"Berlin, Germany"`). | `""` |
| `datePosted` | string | — | Only show jobs posted on or after this date in `YYYY-MM-DD` format (e.g. `"2026-06-01"`). Converts automatically to a freshness window. | No filter |
| `job_type` | string | — | `fulltime`, `parttime`, `contract`, `temporary`, `internship` | Any |
| `is_remote` | boolean | — | Only show remote jobs | `false` |
| `maxItems` | integer | — | Maximum results per keyword (1–10,000) | `20` |

#### Example Input

```json
{
  "keywords": ["software engineer", "data analyst"],
  "location": "San Francisco, California",
  "datePosted": "2026-06-01",
  "job_type": "fulltime",
  "is_remote": false,
  "maxItems": 20
}
```

***

### Output

Each job listing returns a JSON object with the fields below. Fields that depend on employer-provided data (salary, company metadata, skills, etc.) are `null` when not available — only the core identity fields are guaranteed non-null.

#### Core Fields

| Field | Type | Description |
|---|---|---|
| `title` | string | Job title |
| `company` | string | Company name |
| `location` | string | Job location (city, state, or empty) |
| `job_url` | string | LinkedIn job listing URL |
| `job_url_direct` | string? | Employer's own careers page URL for direct applications |
| `id` | string | LinkedIn's persistent job posting ID — stable across runs for deduplication |
| `date_posted` | string | ISO date the job was posted (`YYYY-MM-DD`) |
| `description` | string | Full job description in markdown format (not a truncated preview) |
| `site` | string | Source site (`"linkedin"`) |
| `job_type` | string | `fulltime`, `parttime`, `contract`, `temporary`, `internship` |
| `is_remote` | boolean | Whether the job is remote |
| `job_level` | string | Seniority level (e.g. `"entry level"`, `"mid-senior level"`) |
| `job_function` | string | Job function category (e.g. `"Engineering"`, `"Engineering and Information Technology"`) |

#### Salary Fields

When the employer includes salary information in the listing:

| Field | Type | Description |
|---|---|---|
| `salary_source` | string? | Where the salary data came from (e.g. `"description"` when parsed from the job description) |
| `interval` | string? | Pay interval (e.g. `"yearly"`, `"monthly"`, `"hourly"`) |
| `min_amount` | number? | Minimum of the posted salary range |
| `max_amount` | number? | Maximum of the posted salary range |
| `currency` | string? | ISO 4217 currency code (e.g. `"USD"`) |

#### Company Fields

| Field | Type | Description |
|---|---|---|
| `company_industry` | string? | Industry classification (e.g. `"Software Development"`, `"Financial Services"`) |
| `company_url` | string? | Company's LinkedIn page URL |
| `company_logo` | string? | URL of the company's LinkedIn profile image |

#### Additional Fields

| Field | Type | Description |
|---|---|---|
| `emails` | string? | Email addresses found in the job description |
| `listing_type` | string? | Listing classification (e.g. sponsored, organic) |
| `skills` | string? | Skills mentioned or required in the posting |
| `experience_range` | string? | Years of experience required |
| `vacancy_count` | number? | Number of open positions for this listing |
| `work_from_home_type` | string? | Hybrid/remote classification details |

***

### Use Cases

- **Job seekers** — Monitor fresh listings in your field across multiple keywords and locations in one run. Filter by recency and job type to focus on what matters.
- **Recruiters & staffing agencies** — Build candidate pipeline datasets. Track hiring velocity at target companies. Map the competitive landscape by role and location.
- **Market researchers** — Analyse salary trends, skill demand, and hiring volume. Compare job markets across cities and countries.
- **Sales & lead generation** — Identify companies that are actively hiring for roles your product serves. Time outreach to match growth signals.

***

### FAQ

**Do I need a LinkedIn account?**
No. This scraper runs entirely on residential proxies — no login, no cookies, no account required. Your LinkedIn profile is never involved.

**Can I scrape multiple keywords at once?**
Yes. Submit an array of keywords and each one runs as an independent scrape job. Results are combined into a single dataset, tagged by search term.

**What countries are supported?**
LinkedIn search covers 45+ countries. Include the country in your `location` string (e.g. `"London, United Kingdom"`) for accurate geo-targeting.

# Actor input Schema

## `keywords` (type: `array`):

Job titles or keywords to search for (e.g. 'software engineer', 'data analyst')

## `location` (type: `string`):

City, state, or region to search in (e.g. 'San Francisco', 'Remote')

## `datePosted` (type: `string`):

Filter jobs posted on or after this date (YYYY-MM-DD), or use relative strings like 'week', 'month', '24 hours'

## `job_type` (type: `string`):

Type of employment

## `is_remote` (type: `boolean`):

Only show remote jobs

## `sites` (type: `string`):

Job board to scrape (select one)

## `maxItems` (type: `integer`):

Maximum number of job listings to return

## Actor input object example

```json
{
  "keywords": [
    "software engineer",
    "data analyst"
  ],
  "location": "San Francisco",
  "datePosted": "2026-06-02",
  "job_type": "",
  "is_remote": false,
  "sites": "linkedin",
  "maxItems": 20
}
```

# 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 = {
    "keywords": [
        "software engineer",
        "data analyst"
    ],
    "location": "San Francisco",
    "datePosted": "2026-06-02",
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("data_dino/linkedin-jobs-scraper-pro").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 = {
    "keywords": [
        "software engineer",
        "data analyst",
    ],
    "location": "San Francisco",
    "datePosted": "2026-06-02",
    "maxItems": 20,
}

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

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

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

```

## CLI example

```bash
echo '{
  "keywords": [
    "software engineer",
    "data analyst"
  ],
  "location": "San Francisco",
  "datePosted": "2026-06-02",
  "maxItems": 20
}' |
apify call data_dino/linkedin-jobs-scraper-pro --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=data_dino/linkedin-jobs-scraper-pro",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZWiZjTExSoIU2gXG9/builds/SBosA83OvUhnm0Bju/openapi.json