# LinkedIn Salary Jobs Scraper (`neuton/linkedin-salary-jobs-intelligence`) Actor

Scrape public LinkedIn jobs with disclosed salary text, job criteria, descriptions, and clean fields for compensation benchmarking.

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

## Pricing

$8.00 / 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/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 Salary Jobs Scraper

Scrape public LinkedIn job postings with disclosed compensation text, descriptions, job criteria, companies, and locations for salary benchmarking and talent-market research. No LinkedIn login, cookies, or private-profile access is required.

### What this Actor is for

Use public employer-posted salary data to compare disclosed compensation across roles, locations, companies, seniority levels, and employment types. Set `includeOnlySalaryJobs` to `true` when you want a salary-only dataset instead of retaining jobs whose compensation is not publicly shown.

- Search several job titles and locations in one run
- Keep salary text exactly as publicly displayed instead of inventing missing ranges
- Fetch public descriptions and job criteria for analysis
- Deduplicate overlapping searches by public job ID
- Run cheaply on an HTTP-only 256 MB runtime

### Example input

```json
{
  "queries": ["data scientist"],
  "locations": ["United States"],
  "datePosted": "r2592000",
  "includeOnlySalaryJobs": true,
  "maxResultsPerQuery": 50
}
```

### Output fields

Each job row can include:

- `jobId`, `jobUrl`, `title`, `company`, `companyUrl`, `logoUrl`
- `location`, `searchQuery`, `searchLocation`, `postedAtText`, `postedDate`
- `salaryText`, `description`, `descriptionHtml`
- `workplace_type`, `seniority_level`, `employment_type`, and other public criteria
- `easyApply`, `applyUrl`, `isRemote`, `scrapedAt`

Salary disclosure varies by employer and jurisdiction. The Actor preserves public `salaryText`; it does not estimate, normalize, or infer compensation that LinkedIn does not show.

### Compensation research workflow

Schedule separate Tasks for roles or markets, export CSV/Excel for analysis, or send rows through a webhook to a warehouse. Use `jobId` for deduplication and retain `jobUrl` for source verification. The output can also feed ChatGPT, Claude, n8n, Make, Zapier, BI tools, or the [Neuton Actors MCP Server](https://apify.com/neuton/neuton-actors-mcp-server).

### Pricing

Launch price: $8.00 per 1,000 returned salary-intelligence rows ($0.008 each). A 100-row result set costs about $0.80 in Actor charges. When salary-only mode is enabled, jobs without public salary text are filtered out before results are returned. This is a margin-first price.

### Salary jobs scraper SEO keywords

LinkedIn salary scraper, salary jobs API, compensation benchmarking data, public job salary data, pay transparency research, recruiting market intelligence.

### LinkedIn jobs workflow family

- [LinkedIn Remote Jobs Scraper & Intelligence](https://apify.com/neuton/linkedin-remote-jobs-intelligence) for strict remote-role filtering
- [LinkedIn Easy Apply Jobs Scraper](https://apify.com/neuton/linkedin-easy-apply-jobs-scraper) for in-platform application paths
- [LinkedIn Company Hiring Signals Scraper](https://apify.com/neuton/linkedin-company-hiring-signals) for sales and company-growth research
- [LinkedIn Job Skills Demand Scraper](https://apify.com/neuton/linkedin-tech-skills-demand-analyzer) for technology demand counts

### Responsible use

This Actor processes public job-posting information. Do not use it for spam, unlawful discrimination, automated applications, private-profile collection, access-control bypass, or excessive requests. Verify source postings before compensation or employment decisions. This Actor is not affiliated with or endorsed by LinkedIn.

# Actor input Schema

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

Role, skill, or market queries.

## `locations` (type: `array`):

LinkedIn location text such as United States, London, or Bengaluru.

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

LinkedIn period: r86400, r604800, or r2592000.

## `experienceLevels` (type: `array`):

Optional LinkedIn experience filter codes.

## `jobTypes` (type: `array`):

Optional LinkedIn job type filter codes.

## `geoId` (type: `string`):

Optional LinkedIn geo ID for exact location targeting.

## `maxResultsPerQuery` (type: `integer`):

Maximum public jobs to inspect for each query/location pair.

## `includeOnlySalaryJobs` (type: `boolean`):

Drop jobs where LinkedIn does not expose salary text.

## Actor input object example

```json
{
  "queries": [
    "data scientist"
  ],
  "locations": [
    "United States"
  ],
  "datePosted": "r2592000",
  "experienceLevels": [],
  "jobTypes": [],
  "maxResultsPerQuery": 25,
  "includeOnlySalaryJobs": false
}
```

# Actor output Schema

## `results` (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("neuton/linkedin-salary-jobs-intelligence").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("neuton/linkedin-salary-jobs-intelligence").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 neuton/linkedin-salary-jobs-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuton/linkedin-salary-jobs-intelligence"
        }
    }
}

```

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/XTG68aMa0bKgwUuBr/builds/oMeYIKDzCFgb38tpO/openapi.json