# LinkedIn Jobs Scraper Pro (`martinjoz/linkedin-jobs-scraper`) Actor An automated, headless LinkedIn Jobs scraper that delivers fresh, relevant listings with smart date filtering and enriched contact detailsβ€”completely hassle-free, with all session handling and account safety managed for you - **URL**: https://apify.com/martinjoz/linkedin-jobs-scraper.md - **Developed by:** [Martin Muchene](https://apify.com/martinjoz) (community) - **Categories:** Developer tools, Lead generation, Automation - **Stats:** 3 total users, 1 monthly users, 92.3% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.80 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## πŸ‘” LinkedIn Jobs B2B Leads Extractor **Extract high-quality, targeted job postings and direct company contact data from LinkedIn at scale.** Perfect for B2B Sales, Recruitment Agencies, Market Researchers, and Lead Generation professionals who need fresh, enriched data based on real-time hiring intent. [![Try for Free](https://img.shields.io/badge/Try%20for%20Free-Apify%20Console-blue?style=for-the-badge&logo=apify)](https://apify.com/martinjoz/linkedin-jobs-leads-extractor) [![Documentation](https://img.shields.io/badge/Documentation-Quick%20Start-green?style=for-the-badge)](./QUICK_START.md) --- ### 🎯 What It Does This actor intelligently searches LinkedIn Jobs globally and extracts actionable business intelligence: - βœ… **Standard Info:** Job titles, company names, locations, posting dates, and raw application URLs. - βœ… **Hiring Intel:** Identifies whether it's an "Easy Apply" or external application, plus the exact listed hiring intent. - βœ… **Premium Enrichment:** Validated **Emails**, **Phone Numbers**, and **Contact Pages** automatically extracted from the hiring company's own external website. - βœ… **Real-Time Data:** No stale databases. Every scrape executes live against LinkedIn's public job boards. **Result:** Clean, structured JSON datasets revealing exactly who is hiring, where they are, and *how to contact them directly*. --- ### πŸ’Ž Premium Performance Features | Feature | Description | Benefit | |---------|-------------|---------| | **Contact Enrichment** | Automatically finds and crawls the hiring company's website. | Bypass the LinkedIn message queue and cold email/call decision makers directly. | | **Stealth Extraction** | Uses Playwright with smart throttling and cookie session management. | High reliability for extracting thousands of jobs. | | **Granular Filtering** | Filter by exact keywords, location, and date posted. | Laser-target your ideal leads (e.g., "Only companies in Texas hiring Software Engineers in the last 24 hours.") | | **Automated De-duplication** | Intelligently removes duplicate job postings. | Pay only for unique, valid leads. | --- ### ⚑ Quick Start (5 minutes) 1. **Prepare Input:** Define your desired job titles and locations. 2. **Run the Actor:** Click **Run** on the Apify console. 3. **Download Leads:** Export results as CSV, JSON, or Excel to plug straight into your CRM or cold email tool. --- ### πŸ“Š Input Configuration We've made it simple to get started. Use these "Copy-Paste" templates for common scenarios: #### Option 1: Standard Job Search (No Enrichment) *Best for market research or identifying hiring trends across industries.* ```json { "query": "Marketing Manager", "location": "London, UK", "datePosted": "1week", "limit": 100, "enrichCompanyContacts": false } ```` #### Option 2: Premium B2B Lead Generation (With Contact Enrichment) *Best for B2B Agencies pitching services to companies actively showing hiring intent.* ```json { "query": "VP of Sales", "location": "United States", "datePosted": "1day", "limit": 50, "enrichCompanyContacts": true } ``` #### Advanced Parameters | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `query` | `string` | βœ… Yes | The job title, keyword, or company to search for. | | `location` | `string` | ❌ No | Geographic area to target. | | `limit` | `number` | ❌ No | Max job postings to extract (Default: 50). | | `datePosted` | `string` | ❌ No | Filter by time (`1day`, `3days`, `1week`, `2weeks`). | | `enrichCompanyContacts`| `boolean`| ❌ No | Crawl the hiring company's actual website for Emails and Phone Numbers (Premium). | | `cookies` | `array` | ❌ No | Provide your own LinkedIn cookies for deep authenticated searches. | *** ### πŸ“€ Data Output Intelligence The product returns rich, deeply structured JSON containing full job details, metadata, and (when enabled) premium contact enrichment. #### Complete Output Schema Here is a real example of the data you get for every single extracted job lead: ```json { "jobId": "63", "source": "linkedin", "query": "Software Developer", "searchLocation": "Nairobi", "position": 1, "searchPageUrl": "https://www.linkedin.com/jobs/search/?keywords=Software+Developer&location=Nairobi...", "linkedinJobUrl": "https://ke.linkedin.com/jobs/view/software-engineer-at-solvo-global-...", "title": "Software engineer", "companyName": "Solvo Global", "companyLinkedInUrl": "https://www.linkedin.com/company/solvo-global...", "companyWebsiteUrl": "https://solvoglobal.com", "companyContactEmails": ["recruitment@solvoglobal.com"], "companyContactPhoneNumbers": ["+1-800-555-0199"], "companyContactPages": ["https://solvoglobal.com/contact"], "location": "Nairobi, Nairobi County, Kenya", "workplaceType": "Remote", "employmentType": "FULL_TIME", "seniorityLevel": "Not Applicable", "industries": [ "Transportation", "Logistics", "Supply Chain and Storage" ], "jobFunctions": [ "Engineering and Information Technology" ], "salaryText": "$1,800.00/mo - $2,000.00/mo", "postedAtText": "2 days ago", "datePosted": "2026-04-02T21:10:39.000Z", "validThrough": "2026-05-02T21:10:39.000Z", "applicantsText": "Over 200 applicants", "descriptionText": "General Description~ The Software Engineer designs, develops, tests, and maintains...", "highlightBullets": [ "Collaborate with engineers, product owners, and stakeholders...", "Build and maintain rich client-side experiences with React..." ], "skills": [], "benefits": [], "recruiterName": "Software Engineer - Python - Cloud - graduate level", "applyUrl": "https://www.linkedin.com/login?emailAddress=&fromSignIn=...", "applyMethod": "linkedin", "howToApply": "Open the LinkedIn job page or apply flow.", "emails": [], "phoneNumbers": [], "sourceMetadata": { "Seniority level": "Not Applicable", "Employment type": "Full-time", "Job function": "Engineering and Information Technology", "Industries": "Transportation, Logistics, Supply Chain and Storage" }, "warnings": [], "scrapedAt": "2026-04-09T08:25:30.476Z", "screenshotPath": null, "htmlSnapshotPath": null } ``` *(Note: The `companyWebsiteUrl`, `companyContactEmails`, `companyContactPhoneNumbers`, and `companyContactPages` fields will only populate if you have set `enrichCompanyContacts: true` in your input configuration).* *** ### πŸ’‘ Industry Use Cases & ROI #### πŸ’Ό B2B Agencies & SaaS Companies Target companies that are actively hiring to sell your services (e.g., selling HR software to companies hiring HR Managers; selling marketing services to companies hiring Marketing Directors). - **Cost:** ~$20 for highly enriched leads. - **ROI:** One new booked meeting covers the data cost for months. #### πŸ•΅οΈ Recruitment & Staffing Monitor competitors or identify companies struggling to fill roles (jobs posted >2 weeks ago) to pitch your staffing solutions. - **Cost:** ~$10 per targeted search. - **ROI:** Placing a single candidate ($10K+ fee) = **1,000X ROI**. #### πŸ“ˆ Job Seekers at Scale Automate your job search by scraping all relevant roles daily, exporting to a Google Sheet, and filtering for your exact criteria without mindlessly scrolling LinkedIn. *** ### πŸ’° Pricing: Pay-Per-Event This actor follows the Apify "Pay-Per-Event" model. You only pay for successful, extracted job leads. - **Free Trial:** Test it out with free credits on Apify. - **Predictable Scaling:** You generate leads, we take care of the proxies, unblocking, and compute costs. - **Two-Tier Pricing:** Base price for standard job data; Premium price only if you enable `enrichCompanyContacts`. [View Detailed Pricing Guide](./PRICING_GUIDE.md) *** ### πŸ”§ Integration & Workflow Results are available as **JSON, CSV, or Excel**. Use Apify's integrations to seamlessly push leads directly to: - βœ… **HubSpot / Salesforce / Apollo** - βœ… **Zapier / Make.com** - βœ… **Airtable / Google Sheets** - βœ… **Webhook / API** *** ### πŸ› Support & Compliance - **Support:** Open an issue in the [Support Tab](https://apify.com/martinjoz/linkedin-jobs-leads-extractor/support) or email `martinjozaws@gmail.com`. - **Compliance:** This actor extracts publicly available data. Please respect LinkedIn's Terms of Service and data privacy laws (GDPR/CCPA) when utilizing contact enrichment. **Start your lead generation journey today! πŸš€** # Actor input Schema ## `query` (type: `string`): The target job role (e.g. 'Software Engineer'). ## `location` (type: `string`): Search region (e.g. 'Nairobi', 'Remote'). ## `limit` (type: `integer`): Maximum number of distinct Job URL detail pages to process and enrich. ## `datePosted` (type: `string`): Filter by job posting date. ## `enrichCompanyContacts` (type: `boolean`): Crawl company websites to extract emails/phones. Charges at the enriched-job rate. ## `maxConcurrency` (type: `integer`): Number of job detail pages to scrape simultaneously. ## `cookies` (type: `array`): Pass LinkedIn li\_at cookies to bypass login friction. ## Actor input object example ```json { "limit": 50, "enrichCompanyContacts": true, "maxConcurrency": 3 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("martinjoz/linkedin-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("martinjoz/linkedin-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call martinjoz/linkedin-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=martinjoz/linkedin-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper Pro", "description": "An automated, headless LinkedIn Jobs scraper that delivers fresh, relevant listings with smart date filtering and enriched contact detailsβ€”completely hassle-free, with all session handling and account safety managed for you", "version": "1.0", "x-build-id": "9Hc1E1CNu7YKv8gts" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/martinjoz~linkedin-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-martinjoz-linkedin-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/martinjoz~linkedin-jobs-scraper/runs": { "post": { "operationId": "runs-sync-martinjoz-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/martinjoz~linkedin-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-martinjoz-linkedin-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Job Title / Keyword", "type": "string", "description": "The target job role (e.g. 'Software Engineer')." }, "location": { "title": "Location", "type": "string", "description": "Search region (e.g. 'Nairobi', 'Remote')." }, "limit": { "title": "Max Jobs to Scrape", "minimum": 1, "type": "integer", "description": "Maximum number of distinct Job URL detail pages to process and enrich.", "default": 50 }, "datePosted": { "title": "Date Posted", "enum": [ "1day", "3days", "1week", "2weeks" ], "type": "string", "description": "Filter by job posting date." }, "enrichCompanyContacts": { "title": "Enrich Company Contacts (Premium)", "type": "boolean", "description": "Crawl company websites to extract emails/phones. Charges at the enriched-job rate.", "default": true }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 6, "type": "integer", "description": "Number of job detail pages to scrape simultaneously.", "default": 3 }, "cookies": { "title": "Session Cookies (Optional)", "type": "array", "description": "Pass LinkedIn li_at cookies to bypass login friction." } } }, "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 } } } } } } } } } } ```