# Greenhouse Jobs Scraper (`nexgendata/greenhouse-jobs-scraper`) Actor
Scrape live Greenhouse-hosted job boards by company slug — title, location, departments, offices, posted date, full description HTML, application URL. LinkedIn-Jobs alternative for sourcing tools, ATS-competitive intel, sales/BD prospecting target companies, recruiters tracking talent moves.
- **URL**: https://apify.com/nexgendata/greenhouse-jobs-scraper.md
- **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community)
- **Categories:** Jobs, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $50.00 / 1,000 job postings
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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## 🔍 Greenhouse Jobs Scraper — Recruiter & Sales Intel
Scrape live Greenhouse-hosted career boards in bulk. Feed in a list of company slugs, get back every public posting with title, location, departments, offices, posted-date, full description HTML, and application URL — straight from Greenhouse's official open boards API.
Built for **recruiters and sourcing tools** (find candidates by tracking who's hiring), **ATS competitive analysts** (track Greenhouse adoption + posting velocity at target accounts), **sales and BD teams** (prospect into companies that just posted senior roles), and **journalists / analysts** (which startups are growing, hiring freezes, layoffs).
This is a thin wrapper over Greenhouse's public boards API, so the data is fresh, deduplicated, and includes the same fields candidates see on the official board.
### What you get per job
- `id`, `internal_job_id`, `requisition_id` — IDs across Greenhouse's systems
- `company`, `company_slug` — display name and the Greenhouse slug you fed in
- `title` — job title (string)
- `location` — primary location string
- `departments`, `department_ids` — array of department names + IDs
- `offices`, `office_locations` — array of office labels + locations
- `absolute_url` — canonical apply URL on the company's Greenhouse board
- `first_published`, `updated_at` — ISO-8601 timestamps
- `language` — usually `"en"`
- `application_deadline` — when present
- `metadata` — any custom fields the company exposes (e.g. seniority, comp band)
- `content_html` — full HTML description (when `includeContent: true`)
- `source` — `"greenhouse.io"`
### Use cases
1. **Recruiter sourcing** — pull every senior IC role at 50 high-growth Series-B startups, filter for keywords in the description, get a daily diff via [Apify Schedules](https://apify.com/docs/scheduler).
2. **ATS competitive intel** — count Greenhouse postings per company per week to track hiring velocity vs. Lever or Workday.
3. **Sales prospecting** — companies that just opened a "Head of Revenue Operations" role are buying CRM/CDP tooling now.
4. **Talent platform aggregator** — feed your job board with tens of thousands of postings from the companies you cover.
5. **Comp-band benchmarking** — many GH boards publish salary ranges in the description; extract them downstream.
6. **Investor due-diligence** — track headcount growth at portfolio companies via job-posting cadence.
### Quick start
Input:
```json
{
"companies": ["stripe", "airbnb", "notion"],
"maxJobs": 100,
"includeContent": true
}
````
Sample output row:
```json
{
"id": 7532733,
"internal_job_id": 3336216,
"requisition_id": null,
"company": "Stripe",
"company_slug": "stripe",
"title": "Software Engineer, Issuing Platform",
"location": "San Francisco, CA",
"departments": ["Engineering"],
"offices": ["South San Francisco HQ", "Remote North America"],
"absolute_url": "https://stripe.com/jobs/search?gh_jid=7532733",
"first_published": "2024-09-12T18:32:14Z",
"updated_at": "2025-04-22T14:20:01Z",
"content_html": "Stripe is the financial infrastructure...
",
"source": "greenhouse.io"
}
```
### Run via Python (apify-client)
```python
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/greenhouse-jobs-scraper").call(
run_input={
"companies": ["stripe", "airbnb", "notion"],
"maxJobs": 500,
"includeContent": True,
}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item["title"], "-", item["company"], "-", item["location"])
```
### Run via cURL
```bash
curl -X POST "https://api.apify.com/v2/acts/nexgendata~greenhouse-jobs-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"companies":["stripe","notion"],"maxJobs":50,"includeContent":false}'
```
### Integrations
- **Zapier** — trigger on each new posting and create a row in Airtable / Notion / a Slack alert.
- **Make.com** — chain into HubSpot or Salesforce as new prospect signals.
- **n8n** — schedule + dedupe + push into Postgres for trend analysis.
### Pricing
Pay-per-event (PPE):
- **Actor start:** $0.00005 (negligible)
- **Per job posting:** **$0.05**
Cost calculator:
| Jobs returned | Cost |
| --- | --- |
| 10 (smoke test) | $0.50 |
| 100 | $5.00 |
| 1,000 | $50.00 |
| 5,000 (multi-company sweep) | $250.00 |
That's an order of magnitude cheaper than LinkedIn Recruiter seats for the same hiring-signal data, and you only pay for jobs you actually receive.
### FAQ
**Q: Where do I find the Greenhouse slug?**
A: Go to the company's careers page. If the URL contains `boards.greenhouse.io/{slug}` (or the page redirects there), `{slug}` is what you want.
**Q: Does this work for any company?**
A: Only companies hosted on Greenhouse Boards. Lever, Ashby, Workday, and SmartRecruiters need different actors — see Related Actors below.
**Q: How fresh is the data?**
A: Greenhouse's API is the source of truth — postings appear here within minutes of the company adding them.
**Q: Do I need a Greenhouse API key?**
A: No. The Boards API is open. There's no rate limit you'll realistically hit at scraper-scale usage.
**Q: Will I get duplicate rows when scraping the same company twice?**
A: Each call is a fresh snapshot. Use `id` as the deduplication key on your side.
**Q: Can I get just the metadata without the full description?**
A: Yes — set `includeContent: false`. Cuts the row size by 80–95%.
### Related actors
- [Lever Jobs Scraper](https://apify.com/nexgendata/lever-jobs-scraper) — same shape, for Lever-hosted boards.
- [WeWorkRemotely Jobs Scraper](https://apify.com/nexgendata/weworkremotely-jobs-scraper) — remote-first job aggregator.
- [HN Who's Hiring Scraper](https://apify.com/nexgendata/hn-whos-hiring-scraper) — monthly Hacker News hiring threads, perfect complement for senior-eng sourcing.
***
Built and maintained by [NexGenData](https://apify.com/nexgendata?fpr=2ayu9b) — affordable, focused web scrapers for B2B data teams.
# Actor input Schema
## `companies` (type: `array`):
List of Greenhouse-hosted company slugs to scrape. The slug is the path segment in `https://boards.greenhouse.io/{slug}` (e.g. `stripe`, `airbnb`, `notion`). Look up the company's careers page if you're not sure of the slug — it usually redirects to a Greenhouse-hosted board.
## `maxJobs` (type: `integer`):
Maximum total number of job postings to return across all companies (1–5000). The default 100 is a safe smoke-test size; raise for full sweeps.
## `includeContent` (type: `boolean`):
If checked, includes the full job description HTML on each row (~5–30 KB per job). Uncheck for slim metadata-only output.
## Actor input object example
```json
{
"companies": [
"stripe",
"figma",
"discord"
],
"maxJobs": 100,
"includeContent": true
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"companies": [
"stripe",
"figma",
"discord"
],
"maxJobs": 100,
"includeContent": true
};
// Run the Actor and wait for it to finish
const run = await client.actor("nexgendata/greenhouse-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"companies": [
"stripe",
"figma",
"discord",
],
"maxJobs": 100,
"includeContent": True,
}
# Run the Actor and wait for it to finish
run = client.actor("nexgendata/greenhouse-jobs-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"companies": [
"stripe",
"figma",
"discord"
],
"maxJobs": 100,
"includeContent": true
}' |
apify call nexgendata/greenhouse-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=nexgendata/greenhouse-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Greenhouse Jobs Scraper",
"description": "Scrape live Greenhouse-hosted job boards by company slug — title, location, departments, offices, posted date, full description HTML, application URL. LinkedIn-Jobs alternative for sourcing tools, ATS-competitive intel, sales/BD prospecting target companies, recruiters tracking talent moves.",
"version": "0.0",
"x-build-id": "2a3aMDWY0dKUcY4Rh"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/nexgendata~greenhouse-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-nexgendata-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/nexgendata~greenhouse-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-nexgendata-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/nexgendata~greenhouse-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-nexgendata-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"companies"
],
"properties": {
"companies": {
"title": "Greenhouse company slugs",
"type": "array",
"description": "List of Greenhouse-hosted company slugs to scrape. The slug is the path segment in `https://boards.greenhouse.io/{slug}` (e.g. `stripe`, `airbnb`, `notion`). Look up the company's careers page if you're not sure of the slug — it usually redirects to a Greenhouse-hosted board.",
"items": {
"type": "string"
}
},
"maxJobs": {
"title": "Max jobs total",
"minimum": 1,
"maximum": 5000,
"type": "integer",
"description": "Maximum total number of job postings to return across all companies (1–5000). The default 100 is a safe smoke-test size; raise for full sweeps.",
"default": 100
},
"includeContent": {
"title": "Include full description HTML",
"type": "boolean",
"description": "If checked, includes the full job description HTML on each row (~5–30 KB per job). Uncheck for slim metadata-only output.",
"default": true
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```