# Naukri.com Job Scraper (`unfenced-group/naukri-scraper`) Actor
Scrape Naukri.com for structured Indian job data: titles, companies, salary ranges, required skills & full descriptions. 100,000+ listings with keyword, location, experience level and work-mode filters. Remote/hybrid/on-site detection. No API key required.
- **URL**: https://apify.com/unfenced-group/naukri-scraper.md
- **Developed by:** [Unfenced Group](https://apify.com/unfenced-group) (community)
- **Categories:** Jobs, Developer tools, Automation
- **Stats:** 15 total users, 5 monthly users, 98.6% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.98 / 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 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
## Naukri.com Job Scraper
Extract structured job listings from [Naukri.com](https://www.naukri.com) — India's largest job portal with 100M+ listings across all major cities. No account required.
---
### What you get
Each result includes:
- **Title, company, locations** — with AmbitionBox rating and review count when available
- **Salary** — structured as `salaryMin` / `salaryMax` in INR (or `null` when employer does not disclose)
- **Experience** — `experienceMin` and `experienceMax` in years
- **Skills** — preferred and additional skills extracted per listing
- **Full description** — HTML, plain text, and Markdown for every job
- **Industry and function area** — standardised Naukri taxonomy
- **Work mode** — `remote`, `hybrid`, `on-site`, or `null`
- **Repost detection** — 90-day cross-run memory to flag duplicate listings in scheduled runs
---
### Input parameters
| Parameter | Type | Description | Default |
|-----------|------|-------------|---------|
| `keyword` | string | Job title or skill, e.g. `python developer`, `data analyst` | — |
| `location` | string | City filter: `bengaluru`, `mumbai`, `pune`, `delhi`, `noida`, `gurgaon`, `hyderabad`, `chennai`, `kolkata`, `ahmedabad` | — (all cities) |
| `jobIds` | array | Specific Naukri job IDs to fetch directly. Overrides `keyword` and `location` | — |
| `daysOld` | integer | Only return jobs posted within this many days, e.g. `7` for last week | — |
| `maxResults` | integer | Maximum number of results to return | `1000` |
| `skipReposts` | boolean | Skip listings already scraped in a previous run | `false` |
---
### Output schema
```json
{
"id": "230326500198",
"url": "https://www.naukri.com/job-listings-senior-software-engineer-...",
"title": "Senior Software Engineer",
"company": "Steris",
"companyId": "12345",
"companyRating": 4.1,
"companyReviewCount": 312,
"locations": ["Pune"],
"salaryText": "15-25 Lacs PA",
"salaryMin": 1500000,
"salaryMax": 2500000,
"salaryCurrency": "INR",
"salaryPeriod": "yearly",
"experienceText": "5-10 Yrs",
"experienceMin": 5,
"experienceMax": 10,
"workMode": "hybrid",
"skills": ["Selenium", "NUnit", "JIRA", "Performance testing"],
"jobType": null,
"industry": "Medical Devices & Equipment",
"functionArea": "Engineering - Software & QA",
"roleCategory": "Software Development",
"noOfOpenings": 1,
"education": "Any Graduate",
"applicationDeadline": null,
"publishDateISO": "2026-03-23T00:00:00+00:00",
"description": "...
",
"descriptionText": "We are looking for a Senior Software Engineer...",
"descriptionMarkdown": "### Position Summary\n\nWe are looking...",
"isRepost": false,
"originalPublishDate": null,
"originalUrl": null,
"source": "naukri.com",
"scrapedAt": "2026-03-30T16:56:37+00:00",
"contentHash": "a3f1b2c9"
}
````
***
### 💰 Pricing
**$0.98 per 1,000 results** — you only pay for successfully retrieved listings. Failed retries and filtered reposts are never charged.
| Results | Cost |
|---------|------|
| 100 | ~$0.10 |
| 1,000 | ~$0.98 |
| 10,000 | ~$9.80 |
| 100,000 | ~$98.00 |
> Flat-rate alternatives typically charge $29–$49/month regardless of usage.
> At 10,000 results/month, this scraper costs significantly less with no commitment.
Use the **Max results** cap in the input to control your spend exactly.
***
### Performance
| Scenario | Results | Duration |
|----------|---------|----------|
| 1 city, 1 keyword | 15–100 | 5–30 seconds |
| All cities, 1 keyword | 50–500 | 30–120 seconds |
| 1,000 results | ~1,000 | 60–180 seconds |
City-specific searches are fastest. Performance depends on how many listings match the keyword across Naukri's sitemaps.
***
### Example use cases
- **Recruitment analytics** — Track salary ranges and required skills by role across Indian cities
- **Market research** — Monitor hiring trends, emerging technologies, and demand by function area
- **Competitive intelligence** — Follow competitor hiring activity by company
- **Job aggregation** — Build or enrich a job board with structured Naukri listings
- **Scheduled monitoring** — Run daily with `skipReposts: true` to capture only new postings
***
### Notes
- `applyUrl` is always `null` — Naukri uses a modal for applications without a direct link
- Salary is often not disclosed by employers; `salaryMin` / `salaryMax` will be `null` in those cases
- `workMode` values: `remote`, `hybrid`, `on-site`, or `null` when not specified
- Jobs outside major cities appear in OtherCities sitemaps and are included when no location filter is set
***
*Built by [unfenced-group](https://apify.com/unfenced-group) · Issues? Open a ticket or send a message.*
# Actor input Schema
## `keyword` (type: `string`):
Job title or skill to search. Example: "python developer", "data analyst". Matched against job URL slugs from Naukri's sitemap.
## `location` (type: `string`):
Filter by city. Supported: Bengaluru, Mumbai, Pune, Delhi, Noida, Gurgaon, Hyderabad, Chennai, Kolkata, Ahmedabad. Leave empty for all cities.
## `jobIds` (type: `array`):
List of specific Naukri job IDs to fetch directly. When provided, keyword and location are ignored.
## `daysOld` (type: `integer`):
Only include jobs posted within this many days. Example: 7 = last week, 30 = last month.
## `maxResults` (type: `integer`):
Maximum number of job listings to return. Default: 1,000.
## `skipReposts` (type: `boolean`):
Skip job listings already scraped in a previous run (90-day cross-run memory).
## Actor input object example
```json
{
"keyword": "python developer",
"jobIds": [],
"maxResults": 50,
"skipReposts": 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keyword": "python developer",
"jobIds": [],
"maxResults": 50,
"skipReposts": false
};
// Run the Actor and wait for it to finish
const run = await client.actor("unfenced-group/naukri-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 = {
"keyword": "python developer",
"jobIds": [],
"maxResults": 50,
"skipReposts": False,
}
# Run the Actor and wait for it to finish
run = client.actor("unfenced-group/naukri-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 '{
"keyword": "python developer",
"jobIds": [],
"maxResults": 50,
"skipReposts": false
}' |
apify call unfenced-group/naukri-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=unfenced-group/naukri-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Naukri.com Job Scraper",
"description": "Scrape Naukri.com for structured Indian job data: titles, companies, salary ranges, required skills & full descriptions. 100,000+ listings with keyword, location, experience level and work-mode filters. Remote/hybrid/on-site detection. No API key required.",
"version": "1.0",
"x-build-id": "evTFYP3MjSnRdMr2Z"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/unfenced-group~naukri-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-unfenced-group-naukri-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/unfenced-group~naukri-scraper/runs": {
"post": {
"operationId": "runs-sync-unfenced-group-naukri-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/unfenced-group~naukri-scraper/run-sync": {
"post": {
"operationId": "run-sync-unfenced-group-naukri-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"keyword": {
"title": "Search keyword",
"type": "string",
"description": "Job title or skill to search. Example: \"python developer\", \"data analyst\". Matched against job URL slugs from Naukri's sitemap."
},
"location": {
"title": "City / Location",
"type": "string",
"description": "Filter by city. Supported: Bengaluru, Mumbai, Pune, Delhi, Noida, Gurgaon, Hyderabad, Chennai, Kolkata, Ahmedabad. Leave empty for all cities."
},
"jobIds": {
"title": "Job IDs (direct fetch)",
"type": "array",
"description": "List of specific Naukri job IDs to fetch directly. When provided, keyword and location are ignored."
},
"daysOld": {
"title": "Days old (recency filter)",
"type": "integer",
"description": "Only include jobs posted within this many days. Example: 7 = last week, 30 = last month."
},
"maxResults": {
"title": "Maximum results",
"minimum": 1,
"type": "integer",
"description": "Maximum number of job listings to return. Default: 1,000.",
"default": 1000
},
"skipReposts": {
"title": "Skip reposts",
"type": "boolean",
"description": "Skip job listings already scraped in a previous run (90-day cross-run memory).",
"default": false
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```