# LinkedIn Jobs Scraper - Listings, Salaries & Details (`scrapercompany/linkedin-jobs-scraper`) Actor

Scrape LinkedIn job search results by keyword and location (title, company, location, posted date, salary, link) with date, distance, Easy Apply and company filters, then full job details: description, salary range, seniority, job type, industries, applicants. No login. Made by ScraperCompany.

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

## Pricing

from $3.00 / 1,000 linkedin jobs pages

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 Jobs Scraper - Listings, Salaries & Details

**LinkedIn Jobs Scraper** by ScraperCompany reads LinkedIn's public job search, the one anyone can see without signing in, in two modes. **Job search** returns up to 10 job cards per page with **title, company, company link and logo, location, posted date, salary (when shown), insights and link**, with LinkedIn's posted-within, distance, Easy Apply, under-10-applicants and company filters, and paging up to 100 pages. **Job details** returns a posting's **full description (plain text and clean HTML), salary range with its label, seniority level, employment type, job function, industries, applicant count, closed flag and numeric company id**. Pricing is pay-per-event: **$0.003 per results page or job**; failed requests and empty pages are not charged.

Proxies, retries and anti-bot handling are built in, so you don't need your own proxies or an API key. Start a run, get structured JSON.

### What can this LinkedIn scraper do?

- **Job search** by keywords and location, up to 100 pages of 10 jobs.
- Filters: **posted within** (day, week, month), **distance**, **Easy Apply**, **fewer than 10 applicants**, **company ids**, LinkedIn **geo id**.
- **Job details** by job id or LinkedIn link: description, salary range, seniority, employment type, industries, applicants, closed flag.
- Company ids from Job details feed the company filter of Job search.
- No LinkedIn account, cookies or browser needed. Empty pages are free.

#### Modes

| Mode | What it returns | Price per request |
| --- | --- | --- |
| `jobs` | Job cards for a keyword and location search: title, company, location, posted date, salary, insights, link | $0.003 |
| `job` | Full posting by job id or link: description (text and HTML), salary, seniority, employment type, industries, applicants, company id | $0.003 |

### Use cases for LinkedIn data

- **Recruiters**: Watch new postings for the roles and cities you hire in.
- **Job-market analysts**: Measure hiring demand, seniority mix and advertised pay by role and region.
- **Sales teams**: Find companies that are hiring for the teams you sell to.

### What LinkedIn data can you extract?

| Field | Description |
| --- | --- |
| `jobs_results[].job_id / title / company / location` | The job card |
| `jobs_results[].posted_at / posted` | Posting date and LinkedIn's relative age |
| `jobs_results[].salary / insights` | Salary when shown, and LinkedIn's insights (e.g. "Actively Hiring") |
| `jobs_results[].link / company_url / company_logo` | Links |
| `next_page` | Next page number (null on the last page) |
| `job.description / description_html` | Full description (Job details) |
| `job.salary / salary_label` | Pay range and who provided it (Job details) |
| `job.seniority_level / employment_type / industries / job_function` | Criteria (Job details) |
| `job.applicants / closed / company_id` | Applicants, closed flag, company id (Job details) |

Every dataset item also carries `input` (the exact request that was sent), `request_id` (quote it to support), `billed` and `scraped_at`.

### How to scrape LinkedIn jobs

1. Open LinkedIn Jobs Scraper in Apify Console and go to the **Input** tab.
2. Enter job searches and a location, and set **Pages per query** for more results. For full postings, switch **Mode** to Job details and paste job ids or links.
3. Adjust the options if needed. Dates accept an exact date (`2026-12-01`) or a relative one (`30 days` from today), so saved tasks and schedules never go stale.
4. Click **Start** and wait for the run to finish.
5. Download the results from the **Output** tab as JSON, CSV, Excel or HTML, or fetch them with the Apify API.

### Input example

This is the default input; running the Actor without changes uses it.

```json
{
  "mode": "jobs",
  "queries": [
    "data analyst"
  ],
  "location": "Toronto, Ontario, Canada",
  "maxPages": 1,
  "jobIds": [
    "4464227292"
  ],
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}
```

### Output example

One dataset item per request (trimmed here; real items contain every field the API returns):

```json
{
  "mode": "jobs",
  "endpoint": "/v1/linkedin/jobs",
  "input": {
    "keywords": "python developer",
    "location": "United States"
  },
  "jobs_results": [
    {
      "company": "Andreessen Horowitz",
      "company_logo": "https://media.licdn.com/dms/image/v2/D560BAQFs3wvS2NM10g/company-logo_100_100/B56ZaiHxu.GoAc-/0/1746476670161/a16z_logo?e=2147483647&v=beta&t=sAyMO5tlSPsBt9w...",
      "company_url": "https://www.linkedin.com/company/a16z",
      "insights": [
        "Actively Hiring"
      ],
      "job_id": "4458251161",
      "link": "https://www.linkedin.com/jobs/view/4458251161/",
      "location": "San Francisco, CA",
      "posted": "17 hours ago",
      "posted_at": "2026-10-06",
      "title": "Software Engineer, Backend (Partner 16, Partner 18)"
    },
    {
      "company": "Synechron",
      "company_logo": "https://media.licdn.com/dms/image/v2/D4E0BAQGU3XDmI-XtZg/company-logo_100_100/B4EZbozLqWHcAU-/0/1747662453848/synechron_logo?e=2147483647&v=beta&t=967JcOKqVU...",
      "company_url": "https://www.linkedin.com/company/synechron",
      "insights": [
        "Actively Hiring +8 benefits"
      ],
      "job_id": "4464227292",
      "link": "https://www.linkedin.com/jobs/view/4464227292/",
      "location": "Jersey City, NJ",
      "posted": "3 weeks ago",
      "posted_at": "2026-09-11",
      "title": "Python Developer"
    }
  ],
  "meta": {
    "elapsed_s": 0.47,
    "source": "linkedin"
  },
  "next_page": 2,
  "search_parameters": {
    "easy_apply": true,
    "engine": "linkedin_jobs",
    "keywords": "python developer",
    "location": "United States",
    "page": 1
  },
  "total": 2,
  "request_id": "req_3f9c0d6e2b8a4c1f9e7d5b3a1c0e8f6d",
  "billed": true,
  "scraped_at": "2026-10-01T14:03:27.512Z"
}
```

A request that fails is saved with an `error` message instead (turn off **Include failed requests** to skip those). Failed requests are never charged.

### How much does it cost to scrape LinkedIn jobs?

This Actor uses **pay-per-event** pricing: you pay for successful API requests, not for compute time.

| Event | Charged when | Price | Per 1,000 |
| --- | --- | --- | --- |
| `search-page` | One page of LinkedIn job search results (up to 10 jobs). Empty pages are free. | $0.003 | $3.00 |
| `job-detail` | One posting's full details: description, salary, seniority, employment type, industries, applicants. | $0.003 | $3.00 |

For example, 1,000 requests in the default mode cost **$3.00**.

- Failed requests (errors, invalid input, blocked upstream after retries) are **free**.
- Requests where the source returns nothing at all (no results, nothing priced) are saved but **not charged**.
- Set **Maximum cost per run** when you start a run and the Actor stops cleanly before going over it.

### FAQ

#### Do I need proxies or an API key?

No. Proxy rotation, retries and anti-bot handling are built in, and the Actor is ready to run as is. You only pay the per-event prices above.

#### Do I need a LinkedIn account?

No. The Actor reads the job search and posting pages LinkedIn shows to signed-out visitors, so no account, cookies or session is used.

#### Why are job type, experience level and remote filters missing?

LinkedIn ignores them on signed-out searches, so offering them would return unfiltered results. Filter on `employment_type` and `seniority_level` from Job details instead.

#### How many jobs can one search return?

LinkedIn serves up to 100 pages of 10 jobs per search. Split broad searches by location or posting date to go further.

#### Is it legal to scrape LinkedIn jobs?

The Actor collects publicly available information that anyone can see without logging in. You are responsible for how you use the results: respect the source site's terms, copyright and privacy law (such as GDPR) and do not collect personal data without a lawful basis. If in doubt, ask a lawyer.

#### What happens when a request is blocked or rate-limited?

Rate limits (HTTP 429) and temporary errors (5xx) are retried automatically with exponential backoff, respecting `Retry-After`. If a request still fails it is saved with the error message and not charged, and the rest of the batch keeps going. A run only fails when every request failed.

#### Why did a request return an error?

Read the `error` field: validation problems (for example a malformed date or an unknown id) are reported exactly as the API sees them. Fix the input and run again; failed requests cost nothing.

#### How many requests can I run at once?

Any number per run. The Actor sends up to 3 requests in parallel by default (change it under **Run options**); larger batches simply take longer.

### Use it from your code

Call the Actor from any language through the [Apify API](https://docs.apify.com/api/v2). With the JavaScript client (`npm install apify-client`):

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

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('scrapercompany/linkedin-jobs-scraper').call({
    "mode": "jobs",
    "queries": [
        "data analyst"
    ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

With Python (`pip install apify-client`):

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("scrapercompany/linkedin-jobs-scraper").call(run_input={
    "mode": "jobs",
    "queries": ["data analyst"],
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

You can also schedule runs, chain them with webhooks, or connect them to Make, Zapier, n8n, Google Sheets and other integrations from the **Integrations** tab.

### Related scrapers

- [Indeed Scraper](https://apify.com/scrapercompany/indeed-jobs-scraper): the same roles on Indeed
- [Careers Page Jobs Scraper](https://apify.com/scrapercompany/careers-page-jobs-scraper): every opening straight from a company's own careers site

### Support

Questions, a field you need, or a site that stopped working? Open an issue on the **Issues** tab. Include the `request_id` from the dataset item so we can trace the request.

# Changelog

This Actor's version history is a separate document: https://apify.com/scrapercompany/linkedin-jobs-scraper/changelog.md

# Actor input Schema

## `mode` (type: `string`):

Search LinkedIn jobs by keyword and location, or read the full details of known postings.

## `queries` (type: `array`):

What: job title, skill or company words, one search per line, e.g. <code>data analyst</code>, <code>registered nurse</code>.

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

Where: a country, state or city, e.g. <code>London, England, United Kingdom</code>. Without a location LinkedIn answers United States results.

## `maxPages` (type: `integer`):

How many result pages (10 jobs each) to fetch for each search (1-100). Each page is a separate request and is charged separately; paging stops at the last page LinkedIn has.

## `jobIds` (type: `array`):

One posting per line: the numeric job id (<code>job_id</code> from Job search results) or a LinkedIn job link such as <code>linkedin.com/jobs/view/4464227292/</code>.

## `posted_within` (type: `string`):

Only postings from this period.

## `distance_miles` (type: `integer`):

Radius around the location: one of <code>0</code> (exact location), <code>5</code>, <code>10</code>, <code>25</code>, <code>50</code> or <code>100</code>. Other values are rejected.

## `easy_apply` (type: `boolean`):

Only postings with LinkedIn Easy Apply.

## `under_10_applicants` (type: `boolean`):

Only postings with fewer than 10 applicants so far.

## `geo_id` (type: `string`):

LinkedIn's numeric <code>geoId</code> from a linkedin.com jobs search link (e.g. <code>103644278</code> United States, <code>101174742</code> Canada). Pins the place when the free-text location is ambiguous.

## `companyIds` (type: `array`):

Only jobs at these companies: LinkedIn numeric company ids (<code>job.company_id</code> in Job details results), up to 20.

## `page` (type: `integer`):

Result page to start from (1-100).

## `customRequests` (type: `array`):

Optional list of JSON objects, one request each, using the API field names shown above. Each object is merged over the options above, so you only need to give what differs. Add <code>"mode": "job"</code> with a <code>job_id</code> to mix in job details. Example: <code>{"keywords":"nurse","location":"Austin, Texas","distance_miles":25,"posted_within":"week"}</code>

## `includeErrors` (type: `boolean`):

When on, a request that fails (for example an unknown property id) is saved as a dataset item with an <code>error</code> message so you can see what went wrong. Failed requests are never charged.

## `maxConcurrency` (type: `integer`):

How many API requests run at the same time (1-8). Parallel runs share one limit, so extra requests wait for a free slot instead of failing.

## `maxRetries` (type: `integer`):

Retries for rate limits (HTTP 429), temporary server errors (5xx) and network errors, with exponential backoff. Validation errors are never retried.

## Actor input object example

```json
{
  "mode": "jobs",
  "queries": [
    "data analyst"
  ],
  "location": "Toronto, Ontario, Canada",
  "maxPages": 1,
  "jobIds": [
    "4464227292"
  ],
  "easy_apply": false,
  "under_10_applicants": false,
  "page": 1,
  "includeErrors": true,
  "maxConcurrency": 3,
  "maxRetries": 2
}
```

# Actor output Schema

## `results` (type: `string`):

One dataset item per request.

## `summary` (type: `string`):

Counts of succeeded, failed, skipped and charged requests.

# 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 = {
    "queries": [
        "data analyst"
    ],
    "location": "Toronto, Ontario, Canada",
    "jobIds": [
        "4464227292"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapercompany/linkedin-jobs-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 = {
    "queries": ["data analyst"],
    "location": "Toronto, Ontario, Canada",
    "jobIds": ["4464227292"],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapercompany/linkedin-jobs-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 '{
  "queries": [
    "data analyst"
  ],
  "location": "Toronto, Ontario, Canada",
  "jobIds": [
    "4464227292"
  ]
}' |
apify call scrapercompany/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapercompany/linkedin-jobs-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/3Pa39Gd0wh9F0nwuj/builds/lH3d7disy8xThZYN7/openapi.json