# LinkedIn Jobs Scraper with Hiring Signals (`teslagp/linkedin-jobs-hiring-signals-scraper`) Actor

- **URL**: https://apify.com/teslagp/linkedin-jobs-hiring-signals-scraper.md
- **Developed by:** [Juan Galeano Patiño](https://apify.com/teslagp) (community)
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $0.60 / 1,000 job posting listeds

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 with Hiring Signals

Scrape LinkedIn job postings worldwide with full descriptions, salary, applicants, and rank companies by open positions to detect active hiring.

### What it does

Extracts job postings from LinkedIn's public guest API without requiring login or cookies. Optionally enriches each posting with full description, salary range, applicant count, and seniority level. Produces two datasets: a primary dataset of individual job postings and a secondary dataset ranking companies by open positions with a hiring signal strength indicator. Works globally — any country, city, or remote.

### Why it's different

- **Hiring signals** — ranks companies by open positions with signalStrength (low/medium/high). Not available in most LinkedIn scrapers.
- **Applicants count** — includes applicant numbers when LinkedIn exposes them. Unique differentiator.
- **Global coverage, no login** — uses LinkedIn's public guest endpoint. Works for any location, no LinkedIn account needed.

### Usage examples

#### Example 1 — SDR hiring surge (US)

```json
{
  "keywords": "sdr",
  "location": "United States",
  "datePosted": "past-month",
  "maxItems": 500,
  "enrichDetails": true,
  "generateHiringSignals": true
}
```

Expected: several hundred jobs and 300+ companies ranked, with top employers showing multiple open positions and signalStrength: medium or high.

Note: for maxItems greater than 1,000, enable the datacenter proxy option in the input to avoid LinkedIn throttling.

#### Example 2 — Remote roles globally

```json
{
  "keywords": "react developer",
  "location": "Remote",
  "datePosted": "past-week",
  "maxItems": 300,
  "enrichDetails": true,
  "generateHiringSignals": true
}
```

#### Example 3 — Quick market exploration (cheaper mode)

```json
{
  "keywords": "data engineer",
  "location": "Austin, TX",
  "datePosted": "past-month",
  "maxItems": 200,
  "enrichDetails": false,
  "generateHiringSignals": true
}
```

This example shows the cheaper mode (without enrichment) for quick exploration of a specific market.

### Output schema

#### Jobs dataset (default, 15 fields)

| Field | Type | Description |
|-------|------|-------------|
| jobId | string | LinkedIn job posting ID |
| title | string | Job title |
| company | string | Company name |
| companyUrl | string | LinkedIn company page URL |
| location | string | Job location |
| postedAt | string | Posting date (ISO) |
| jobUrl | string | Direct link to job posting |
| description | string (nullable) | Full job description |
| seniority | string (nullable) | Seniority level |
| employmentType | string (nullable) | Employment type |
| salary | string (nullable) | Salary range |
| applicants | string (nullable) | Applicant count |
| daysSincePosted | number (nullable) | Days since posting |
| enriched | boolean | Whether enrichment ran |
| scrapedAt | string | Extraction timestamp (ISO) |

#### Hiring signals dataset (named, 11 fields)

| Field | Type | Description |
|-------|------|-------------|
| company | string | Company name |
| companyUrl | string | LinkedIn company page URL |
| openPositions | number | Number of open positions found |
| jobIds | array\[string] | IDs of jobs for this company |
| titles | array\[string] | Titles of open positions |
| locations | array\[string] | Unique locations for this company |
| avgDaysSincePosted | number (nullable) | Average days since posting |
| mostRecentPostingDate | string (nullable) | Most recent posting date |
| topSeniority | string (nullable) | Most common seniority level |
| signalStrength | string (enum) | high | medium | low |
| scrapedAt | string | Extraction timestamp (ISO) |

Note: the hiring-signals dataset is accessed via the Storage tab of the run (named dataset).

### Pricing

| Event | When charged | Price per 1,000 |
|-------|--------------|-----------------|
| Actor start | Per run (automatic) | $0.00005 per run |
| Job listed | Per job extracted | $0.60 |
| Job enriched | Per job successfully enriched | $1.20 |
| Hiring signal | Per company ranked | $0.30 |

A typical run of 1,000 enriched jobs with hiring signals costs approximately $2.04.

### Known limitations

- **Rate limits** — LinkedIn may throttle cookie-less IPs. For runs >1,000 jobs, enable datacenter proxy.
- **Proxy guidance** — datacenter proxy is sufficient for most workloads. Residential proxy is intentionally not used to keep costs predictable for both users and the Actor operator.
- **Sequential pagination** — pages fetched one by one with 300-800ms delay. Large runs take longer.
- **Salary not always available** — only ~20-30% of postings expose salary ranges. Field is null when absent.

### Legal note

Scrapes only public guest endpoints. No cookies or user credentials used. Users are responsible for compliance with LinkedIn's terms and applicable laws.

# Actor input Schema

## `keywords` (type: `string`):

Job search keywords, e.g. 'software engineer' or 'sales manager'.

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

Location to search jobs in

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

Filter by posting date. Maps to LinkedIn's f_TPR param.

## `employmentType` (type: `string`):

Employment type filter.

## `experienceLevel` (type: `string`):

Experience level filter.

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

Maximum number of job postings to scrape

## `enrichDetails` (type: `boolean`):

If enabled, fetches full description, salary, applicants and seniority per job (1 extra request per job; slower and more expensive).

## `generateHiringSignals` (type: `boolean`):

If enabled, writes a second dataset ranking companies by number of open positions found.

## `proxyConfiguration` (type: `object`):

Start without proxies. Enable datacenter proxy only if LinkedIn rate-limits you. Residential is discouraged (developer pays).

## Actor input object example

```json
{
  "location": "United States",
  "datePosted": "past-week",
  "employmentType": "any",
  "experienceLevel": "any",
  "maxItems": 200,
  "enrichDetails": true,
  "generateHiringSignals": true,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("teslagp/linkedin-jobs-hiring-signals-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("teslagp/linkedin-jobs-hiring-signals-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 '{}' |
apify call teslagp/linkedin-jobs-hiring-signals-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,teslagp/linkedin-jobs-hiring-signals-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/6rSH8tXS50rE7dOpc/builds/S2QX0YwghxPKzhsml/openapi.json