# Hiring Signal Intelligence for Job Data (`signal_lab/hiring-signal-intelligence`) Actor

Turn job datasets into explainable company hiring signals for prospecting, recruiting intelligence, and market research.

- **URL**: https://apify.com/signal\_lab/hiring-signal-intelligence.md
- **Developed by:** [Signal Lab](https://apify.com/signal_lab) (community)
- **Categories:** Jobs, Lead generation
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 company signals

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

## Hiring Signal Intelligence

Turn job datasets into a ranked list of companies that are actively hiring. Instead of returning another stream of raw job posts, this Actor groups openings by company, compares adjacent time windows, and explains why each company looks like a meaningful hiring signal.

Use it for **B2B prospecting, recruiting intelligence, market research, and account prioritization**. The analysis is deterministic and does not require an LLM or external API key.

### What this Actor does

- Ranks companies by recent opening volume and growth.
- Measures role diversity, remote-work share, and repeated skills.
- Compares the selected lookback window with the equally long previous window.
- Attaches the underlying job records and plain-language reasons to every score.
- Accepts up to 100,000 source records and returns up to 500 ranked signals.
- Runs with limited Apify permissions and a fixed 256 MB memory ceiling.

This is an analysis Actor, not a job-site scraper. Connect it to an existing job dataset, pass records inline, or call a compatible limited-permission upstream Actor.

### How to use Hiring Signal Intelligence

1. Choose one input source: inline `records`, an Apify `datasetId`, or `sourceActorId` with `sourceActorInput`.
2. Set `lookbackDays`, normally 7–30 days.
3. Set `minOpenings` to exclude companies with weak activity.
4. Set `maxResults` to control the number of paid company signals.
5. Start the Actor and open the default dataset.

Each usable job record needs at least a company and title. Common variants for company, role, location, publication date, URL, and description are normalized automatically.

### Output

One dataset item represents one company signal. It includes `company`, `signalScore`, current and previous opening counts, growth rate, distinct roles, remote share, top skills, reasons, and supporting job records. The `OUTPUT` key-value-store record summarizes source volume and emitted results.

Results can be downloaded as JSON, CSV, Excel, XML, or RSS, accessed through the Apify API, scheduled, or connected to Make, Zapier, webhooks, and other Actors.

### Pricing

This Actor uses transparent pay-per-event pricing:

- **$0.002 per analysis run**
- **$0.005 per emitted company signal**

Examples: 10 company signals cost **$0.052**; 100 signals cost **$0.502**. Runs that find fewer qualified companies cost less. The price covers this Actor's platform usage. If you choose a paid upstream Actor as the data source, that Actor's own charges are separate.

Cloud benchmarks at 256 MB processed 25,000 inline job records in about 7.4 seconds for approximately $0.000225 of platform usage, leaving a safety margin for normal variation.

### When to use another Signal Lab Actor

- Use [Marketplace Deal Alerts](https://apify.com/incandescent_kite/marketplace-deal-alerts) for underpriced listings and price drops.
- Use [Review Pain Intelligence](https://apify.com/incandescent_kite/review-pain-intelligence) for recurring customer complaints with evidence.

### FAQ

#### Does this Actor scrape LinkedIn or job boards?

No. It analyzes records you supply. This keeps the product source-agnostic and lets you use a compliant scraper or your own dataset.

#### Is the score generated by AI?

No. The score is explainable and deterministic. Every factor and supporting job is included in the output.

#### Can it read a private dataset?

Yes. Select the dataset in the input picker. The Actor requests read-only access to that specific dataset and otherwise uses limited permissions.

#### What if no company passes the threshold?

The run succeeds with an empty dataset and a summary explaining how many source records were processed. Lower `minOpenings`, widen `lookbackDays`, or check the date fields.

### Support

If a source field is not recognized or a run behaves unexpectedly, open the Actor's Issues tab and include a small redacted input sample plus the run ID. Do not post API tokens or private datasets.

# Actor input Schema

## `records` (type: `array`):

Inline records for testing or small analyses.

## `datasetId` (type: `string`):

Read job records from this existing Apify dataset.

## `sourceActorId` (type: `string`):

Optional upstream Actor to run. It must support limited permissions; any upstream Actor charges are separate.

## `sourceActorInput` (type: `object`):

JSON input passed to the selected upstream Actor.

## `lookbackDays` (type: `integer`):

Compare this recent window with the equally long preceding window.

## `minOpenings` (type: `integer`):

Do not emit companies with fewer current-window openings.

## `maxResults` (type: `integer`):

Maximum number of ranked company signals to emit.

## `maxSourceItems` (type: `integer`):

Hard cap on records read from an inline array or dataset.

## Actor input object example

```json
{
  "sourceActorInput": {},
  "lookbackDays": 14,
  "minOpenings": 2,
  "maxResults": 50,
  "maxSourceItems": 10000
}
```

# Actor output Schema

## `signals` (type: `string`):

No description

## `summary` (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("signal_lab/hiring-signal-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("signal_lab/hiring-signal-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 signal_lab/hiring-signal-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,signal_lab/hiring-signal-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/2KyEcqgQdxEJkbkj2/builds/GkEQ3scXLZgjLdYJa/openapi.json