# JobSignal – LinkedIn Job Intelligence (`chezsan770/linkedin-job-intelligence-api`) Actor

Turn public LinkedIn job listings into enriched, analytics-ready data with salaries, skills, benefits, workplace type, seniority, deduplication, match scoring, and market summaries. No login or cookies required.

- **URL**: https://apify.com/chezsan770/linkedin-job-intelligence-api.md
- **Developed by:** [Sarthak Kumar](https://apify.com/chezsan770) (community)
- **Categories:** Lead generation, Jobs, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## JobSignal — LinkedIn Job Intelligence API for Apify

JobSignal converts public LinkedIn job listings into clean, enriched, analytics-ready data. It is a cost-efficient TypeScript/Crawlee Apify Actor designed for job boards, recruiting intelligence, lead generation, market research, and automated alerts.

It goes beyond copying HTML:

- Searches by role, skill, location, recency, workplace type, seniority, and contract type.
- Accepts direct public LinkedIn job URLs and search URLs.
- Extracts clean descriptions, company, location, employment type, post date, applicant count, and Easy Apply status.
- Normalizes disclosed hourly, monthly, and annual salary ranges.
- Detects common technical and business skills plus benefits.
- Infers remote/hybrid/on-site status and seniority.
- Generates a stable `fingerprint` for cross-run deduplication and change tracking.
- Adds `matchScore` and `dataQualityScore` fields.
- Produces a run-level market summary with top skills, top companies, remote share, and salary coverage.
- Exports through Apify Dataset API as JSON, CSV, Excel, XML, or RSS.

### Why TypeScript + Crawlee

Apify gives Node.js and TypeScript first-class support. Crawlee supplies production request queues, retries, autoscaling, session/proxy integration, and local/Apify storage with minimal runtime overhead. This Actor deliberately uses HTTP + Cheerio instead of a browser, making typical runs substantially faster and cheaper than Playwright-based scrapers.

### Quick start

Requires Node.js 22+.

```bash
npm install
npm run build
npm test
```

Run locally with Apify CLI:

```bash
apify run
```

Or create `storage/key_value_stores/default/INPUT.json` and run:

```bash
npm run dev
```

Example input:

```json
{
  "searchQueries": ["TypeScript engineer", "AI engineer"],
  "locations": ["United States", "Bengaluru, Karnataka, India"],
  "maxJobs": 250,
  "postedWithin": "pastWeek",
  "workplaceTypes": ["remote", "hybrid"],
  "experienceLevels": ["entry", "mid-senior"],
  "jobTypes": ["full-time", "contract"],
  "includeKeywords": ["LLM", "TypeScript", "Python"],
  "excludeKeywords": ["clearance required"],
  "deduplicate": true,
  "enrichResults": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}
```

### Use as an API

After deploying the Actor, start a run and return dataset items synchronously:

```bash
curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_USERNAME~linkedin-job-intelligence-api/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN&format=json" \
  -H "Content-Type: application/json" \
  -d '{
    "searchQueries": ["backend engineer"],
    "locations": ["London"],
    "maxJobs": 50,
    "postedWithin": "past24h"
  }'
```

For larger runs, use the asynchronous endpoint:

```bash
curl -X POST \
  "https://api.apify.com/v2/acts/YOUR_USERNAME~linkedin-job-intelligence-api/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["data engineer"],"locations":["Germany"],"maxJobs":500}'
```

Then retrieve:

- Jobs: `GET https://api.apify.com/v2/datasets/{defaultDatasetId}/items`
- Summary: `GET https://api.apify.com/v2/key-value-stores/{defaultKeyValueStoreId}/records/OUTPUT`

Keep tokens in secrets or environment variables; never embed them in client-side applications.

### Output record

```json
{
  "id": "123456789",
  "url": "https://www.linkedin.com/jobs/view/123456789",
  "title": "Senior TypeScript Engineer (Remote)",
  "company": "Acme Labs",
  "location": "Bengaluru, India",
  "workplaceType": "remote",
  "employmentType": "Full-time",
  "seniority": "mid-senior",
  "postedAt": "2026-07-25T00:00:00.000Z",
  "descriptionText": "...",
  "salary": {
    "raw": "USD 120,000 - 160,000 per year",
    "min": 120000,
    "max": 160000,
    "currency": "USD",
    "period": "year",
    "annualizedMin": 120000,
    "annualizedMax": 160000
  },
  "skills": ["TypeScript", "React", "Node.js", "AWS"],
  "benefits": ["Health insurance", "Equity"],
  "fingerprint": "d24f...",
  "matchScore": 55,
  "dataQualityScore": 95,
  "source": "linkedin-public"
}
```

Salary parsing only reports a currency when it is stated or represented by an unambiguous symbol. JobSignal does not silently perform foreign-exchange conversion.

### Standout workflows

#### New-job alerts

Schedule the Actor hourly or daily. Store the `fingerprint` values from the prior dataset and alert only on unseen values with an Apify webhook, Make, Zapier, Slack, or email integration.

#### Skills demand radar

Read `OUTPUT.topSkills` after each scheduled run and store snapshots. The series reveals which tools are gaining or losing demand for a role and location.

#### Salary transparency benchmark

Set `minimumSalary` and `salaryCurrency` for precise compensation searches. `salaryCoverage` in the run summary shows how representative the disclosed-salary subset is.

#### ATS / CRM ingestion

Use the stable schema and fingerprints as idempotency keys when writing records to an ATS, CRM, database, or data warehouse.

### Reliability and responsible use

LinkedIn can change its public HTML and rate limits without notice. Production users should:

- Use Apify residential proxies and conservative concurrency.
- Keep retries enabled and schedule smaller incremental runs.
- Monitor `failedRequests` and `dataQualityScore`.
- Update selectors and fixture tests when source markup changes.

To satisfy post-extraction filters without returning a thin result set, JobSignal may inspect up to three times `maxJobs` candidates (capped at 5,000) and stops writing as soon as `maxJobs` accepted records are reached.

This Actor accesses public job pages only. It does not log in, solve CAPTCHAs, scrape profiles, or bypass access controls. You are responsible for ensuring that your use complies with LinkedIn's terms, robots rules, privacy laws, employment laws, and the rules applicable in your jurisdiction. Collect only data you have a lawful reason to process, respect deletion requests, and avoid discriminatory hiring uses.

### Architecture

```text
Input schema
    │
    ├── search query + filters ──> public search result pages
    └── direct URL ──────────────> public job detail page
                                      │
                                      v
                          parse + normalize + enrich
                                      │
                         filter + fingerprint + dedupe
                                ┌─────┴─────┐
                                v           v
                         Dataset jobs   OUTPUT summary
```

### Deploy to Apify

1. Install and authenticate the Apify CLI: `npm install -g apify-cli` then `apify login`.
2. From this folder, run `apify push`.
3. In Apify Console, select a suitable proxy configuration and test a small run.
4. Add a schedule/webhook if you need recurring feeds.
5. Before publishing in Apify Store, add screenshots, pricing, support details, and validate the Actor against current public markup.

The project includes an Actor definition, input/output schemas, two dataset views, a multi-stage production Dockerfile, and deterministic unit/fixture tests.

### License

MIT. LinkedIn is a trademark of LinkedIn Corporation. This project is independent and is not affiliated with or endorsed by LinkedIn.

# Actor input Schema

## `searchQueries` (type: `array`):

Job titles, skills, or Boolean-style search terms.

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

Cities, countries, or Worldwide.

## `startUrls` (type: `array`):

Optional direct public job/search URLs. When supplied, search queries are ignored.

## `maxJobs` (type: `integer`):

Maximum accepted records per run.

## `postedWithin` (type: `string`):

Only discover jobs posted during the selected time window.

## `sortBy` (type: `string`):

Order LinkedIn search results by recency or relevance.

## `workplaceTypes` (type: `array`):

Limit results to remote, hybrid, or on-site jobs.

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

Limit results to one or more LinkedIn experience levels.

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

Limit results to selected employment and contract types.

## `includeKeywords` (type: `array`):

Keep only jobs whose title, company, location, or description contains at least one keyword.

## `excludeKeywords` (type: `array`):

Reject jobs whose title, company, location, or description contains any keyword.

## `minimumSalary` (type: `integer`):

Reject jobs without a disclosed salary or below this annualized amount.

## `salaryCurrency` (type: `string`):

Three-letter currency used with the minimum salary filter. No FX conversion is guessed.

## `deduplicate` (type: `boolean`):

Remove repeat postings using normalized title + company + location fingerprints.

## `enrichResults` (type: `boolean`):

Extract skills, benefits, salary, seniority, workplace type, and scoring.

## `includeDescriptionHtml` (type: `boolean`):

Include the original job-description HTML alongside normalized plain text.

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

Residential proxies are recommended for stable production runs.

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

Maximum number of LinkedIn requests processed concurrently.

## `requestDelayMs` (type: `integer`):

Adds source-friendly pacing before each request.

## Actor input object example

```json
{
  "searchQueries": [
    "TypeScript developer",
    "AI engineer"
  ],
  "locations": [
    "United States",
    "Bengaluru, Karnataka, India"
  ],
  "startUrls": [],
  "maxJobs": 20,
  "postedWithin": "pastWeek",
  "sortBy": "recent",
  "workplaceTypes": [],
  "experienceLevels": [],
  "jobTypes": [],
  "includeKeywords": [],
  "excludeKeywords": [],
  "salaryCurrency": "USD",
  "deduplicate": true,
  "enrichResults": true,
  "includeDescriptionHtml": false,
  "proxyConfiguration": {
    "useApifyProxy": true
  },
  "maxConcurrency": 20,
  "requestDelayMs": 300
}
```

# Actor output Schema

## `jobs` (type: `string`):

All accepted job records in the default dataset.

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

Run metrics, remote share, salary coverage, top skills, and top companies.

# 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 = {
    "searchQueries": [
        "TypeScript developer",
        "AI engineer"
    ],
    "locations": [
        "United States",
        "Bengaluru, Karnataka, India"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("chezsan770/linkedin-job-intelligence-api").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 = {
    "searchQueries": [
        "TypeScript developer",
        "AI engineer",
    ],
    "locations": [
        "United States",
        "Bengaluru, Karnataka, India",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("chezsan770/linkedin-job-intelligence-api").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 '{
  "searchQueries": [
    "TypeScript developer",
    "AI engineer"
  ],
  "locations": [
    "United States",
    "Bengaluru, Karnataka, India"
  ]
}' |
apify call chezsan770/linkedin-job-intelligence-api --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,chezsan770/linkedin-job-intelligence-api"
        }
    }
}

```

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/bsi7kqc6f2azX4IXN/builds/422kmd10Ul428scbS/openapi.json