# Linkedin Job Scraper (`leadstrategus/apify1-linkedin-job-scraper`) Actor Extract detailed job data from LinkedIn public job search pages using a simple search URL. Capture titles, company info, locations, full descriptions, and apply links. Supports filters, company insights, and location splitting to bypass result limits. Outputs structured data in JSON, CSV, or Excel - **URL**: https://apify.com/leadstrategus/apify1-linkedin-job-scraper.md - **Developed by:** [Komala Maran](https://apify.com/leadstrategus) (community) - **Categories:** Automation, Jobs, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 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 ## LinkedIn Job Scraper A powerful tool to extract comprehensive job data from LinkedIn's public job search pages. Get detailed information including job descriptions, company profiles, application links, and more. ### Getting Started #### Important: Use Incognito Mode This tool scrapes jobs from the **public LinkedIn jobs search page**, which displays different results than a logged-in LinkedIn account. To ensure you get accurate and consistent results: 1. Open a new **Incognito/Private window** in your browser. 2. Go to [LinkedIn Jobs Search](https://www.linkedin.com/jobs/search). 3. Apply your desired filters (Location, Date Posted, Job Type, etc.). 4. **Copy the full URL** from the address bar and paste it into the `urls` input field of this actor. ### Features * **Detailed Job Data:** Extracts title, company, location, seniority level, and employment type. * **Full Descriptions:** Captures the complete job description in both Text and HTML formats. * **Company Insights:** Optionally scrapes company website, description, slogan, and headquarters address. * **Application Links:** Grabs the direct apply URL (including offsite career pages). * **Bypass Limits:** Use the "Split by Location" feature to bypass the 1,000-job limit imposed by LinkedIn. ### Input | Field | Type | Description | | :--- | :--- | :--- | | **urls** | Array | List of public LinkedIn Job Search URLs. | | **count** | Integer | Max number of jobs to scrape (Default: 100). | | **scrapeCompany** | Boolean | Whether to fetch detailed company info (website, description). | | **splitByLocation** | Boolean | Automatically splits search by cities to find more results. | ### Output Sample The actor provides structured data in JSON, CSV, or Excel. Here is a sample of the extracted data: ```json { "id": "4399050171", "trackingId": "LdfgDsAsA8dfk5DoJnroaA==", "refId": "bxbm8iPBwBuTXYKDdSmirg==", "link": "https://in.linkedin.com/jobs/view/coe-digital-engineering-frontend-developer-at-qualitest-4399050171?refId=bxbm8iPBwBuTXYKDdSmirg%3D%3D&trackingId=LdfgDsAsA8dfk5DoJnroaA%3D%3D&position=19&pageNum=0", "title": "CoE - Digital Engineering - Frontend Developer", "companyName": "Qualitest", "companyLinkedinUrl": "https://uk.linkedin.com/company/qualitest?trk=public_jobs_jserp-result_job-search-card-subtitle", "companyLogo": "https://media.licdn.com/dms/image/v2/D560BAQGi4S6swMGzWA/company-logo_100_100/company-logo_100_100/0/1736924694824/qualitest_logo?e=1778112000&v=beta&t=PGeQem2bpN0X_VjJe8fUwU1n6rah5rh5N9t8T2ak4Ho", "location": "Bengaluru, Karnataka, India", "postedAt": "2026-04-14T21:07:56.000Z", "benefits": [ "Actively Hiring" ], "descriptionHtml": "Job Title: Next.js Front-End DeveloperWe are looking for a skilled JavaScript developer with strong experience in Next.js and React.js to join our front-end team. Your primary focus will be on building high-quality, scalable, and performant user interfaces using modern React and Next.js frameworks.You will work closely with designers, backend engineers, and product teams to deliver seamless user experiences. A strong commitment to clean code, performance optimization, and collaborative problem-solving is essential.ResponsibilitiesDevelop new user-facing features using Next.js and React.jsBuild reusable components and front-end libraries for future useImplement server-side rendering (SSR), static site generation (SSG), and API routes using Next.jsTranslate UI/UX designs and wireframes into high-quality, maintainable codeOptimize applications for maximum performance across devices and browsersCollaborate with backend developers to integrate RESTful and/or GraphQL APIsEnsure code quality through best practices, testing, and maintainabilityParticipate in code reviews and contribute to team knowledge sharingRequired SkillsStrong proficiency in JavaScript (ES6+), including DOM manipulation and object modelSolid understanding of React.js and its core principles (hooks, state management, lifecycle)Hands-on experience with Next.js (SSR, SSG, ISR, routing, middleware)Experience with state management libraries (e.g., Redux, Zustand, or Context API)Familiarity with RESTful APIs and asynchronous request handlingUnderstanding of modern authentication methods (e.g., JWT, OAuth)Experience with modern front-end build tools (Webpack, Vite, Babel)Proficiency with package managers like NPM or YarnFamiliarity with version control tools such as GitGood to HaveExperience with TypeScriptFamiliarity with GraphQL and tools like Apollo ClientUnderstanding of SEO best practices in Next.js applicationsExperience with CSS frameworks (Tailwind CSS, Material UI, etc.)Knowledge of testing frameworks (Jest, React Testing Library)Exposure to CI/CD pipelines and deployment platforms (e.g., Vercel, Docker)Soft SkillsAbility to understand business requirements and translate them into technical solutionsStrong problem-solving and debugging skillsAttention to detail with a focus on performance and scalabilityExcellent communication and collaboration skills3 must havesJavaScript developer with strong experience in Next.js and React.js 4/5", "applicantsCount": "200", "applyUrl": "https://careers.qualitestgroup.com/job/Bangalore-CoE-Digital-Engineering-Frontend-Developer-560045/54907444/?utm_source=LINKEDIN&utm_medium=referrer", "salary": "", "descriptionText": "Job Title: Next.js Front-End DeveloperWe are looking for a skilled JavaScript developer with strong experience in Next.js and React.js to join our front-end team. Your primary focus will be on building high-quality, scalable, and performant user interfaces using modern React and Next.js frameworks.You will work closely with designers, backend engineers, and product teams to deliver seamless user experiences. A strong commitment to clean code, performance optimization, and collaborative problem-solving is essential.ResponsibilitiesDevelop new user-facing features using Next.js and React.jsBuild reusable components and front-end libraries for future useImplement server-side rendering (SSR), static site generation (SSG), and API routes using Next.jsTranslate UI/UX designs and wireframes into high-quality, maintainable codeOptimize applications for maximum performance across devices and browsersCollaborate with backend developers to integrate RESTful and/or GraphQL APIsEnsure code quality through best practices, testing, and maintainabilityParticipate in code reviews and contribute to team knowledge sharingRequired SkillsStrong proficiency in JavaScript (ES6+), including DOM manipulation and object modelSolid understanding of React.js and its core principles (hooks, state management, lifecycle)Hands-on experience with Next.js (SSR, SSG, ISR, routing, middleware)Experience with state management libraries (e.g., Redux, Zustand, or Context API)Familiarity with RESTful APIs and asynchronous request handlingUnderstanding of modern authentication methods (e.g., JWT, OAuth)Experience with modern front-end build tools (Webpack, Vite, Babel)Proficiency with package managers like NPM or YarnFamiliarity with version control tools such as GitGood to HaveExperience with TypeScriptFamiliarity with GraphQL and tools like Apollo ClientUnderstanding of SEO best practices in Next.js applicationsExperience with CSS frameworks (Tailwind CSS, Material UI, etc.)Knowledge of testing frameworks (Jest, React Testing Library)Exposure to CI/CD pipelines and deployment platforms (e.g., Vercel, Docker)Soft SkillsAbility to understand business requirements and translate them into technical solutionsStrong problem-solving and debugging skillsAttention to detail with a focus on performance and scalabilityExcellent communication and collaboration skills3 must havesJavaScript developer with strong experience in Next.js and React.js 4/5", "seniorityLevel": "Entry level", "employmentType": "Full-time", "jobFunction": "Engineering and Information Technology", "industries": "IT Services and IT Consulting", "inputUrl": "https://www.linkedin.com/jobs/search?keywords=Aiml%20Engineer&location=Greater%20Bengaluru%20Area&geoId=90009633&f_E=2&f_PP=105214831&f_TPR=r604800&position=1&pageNum=0", "salaryInsights": {}, "applyMethod": "OffsiteApply", "expireAt": 1778792876000, "postedAtTimestamp": 1776200876000, "workplaceTypes": [], "workRemoteAllowed": false, "standardizedTitle": "Frontend Developer", "country": "IN", "companyAddress": { "type": "PostalAddress", "streetAddress": "1 Appold Street London", "addressLocality": "London", "postalCode": "EC2A2UT", "addressCountry": "GB" }, "companyWebsite": "https://www.qualitestgroup.com/", "companySlogan": "Engineering tomorrow with AI, People & Precision.", "companyDescription": "Qualitest is the world’s leading managed services provider of AI-led quality engineering solutions. It helps brands transition through the digital assurance journey and make the move from conventional functional testing to adopt innovations such as automation, AI, blockchain, and XR. \n \nQualitest’s core mission is to mitigate business risks associated with digital adoption. It fulfills this through customized quality engineering solutions that leverage Qualitest’s deep, industry-specific knowledge for various sectors, including technology, telecommunications, finance, healthcare, media, utilities, retail, manufacturing, and defense. These scalable solutions protect brands through end-to-end value demonstration with a focus on customer experience and release velocity. \n \nA pioneer and innovator in its industry, Qualitest has been recognized in the highest Leader position in Everest Group's Quality Engineering Services for Mid-market Enterprises PEAK Matrix® Assessment 2024 report and has also been recognized as a Leader in The Forrester Wave™️: Continuous Automation and Testing Services Q2 2024 report.\n \nQualitest has offices in the United States, United Kingdom, Israel, Romania, India, Mexico, Portugal, Switzerland, and Argentina. ", "companyEmployeesCount": 6056 } ```` ### Pro Tips - **Daily Updates:** To scrape new jobs daily, set the LinkedIn "Date Posted" filter to "Last 24 hours" before copying the URL, then schedule this actor to run once a day. - **Boolean Search:** LinkedIn supports Boolean operators in the keyword field (e.g., `"Frontend" AND "React" NOT "Angular"`) to help refine your results. # Actor input Schema ## `urls` (type: `array`): Paste one or more LinkedIn Job Search URLs here. ## `count` (type: `integer`): Number of jobs to scrape per search URL. ## `scrapeCompany` (type: `boolean`): If enabled, extracts full company descriptions and employee counts. ## `splitByLocation` (type: `boolean`): Enable this to bypass the 1000-job LinkedIn limit by splitting searches into smaller areas. ## Actor input object example ```json { "urls": [ "https://www.linkedin.com/jobs/search/?position=1&pageNum=0" ], "count": 100, "scrapeCompany": true, "splitByLocation": false } ``` # 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 = { "urls": [ "https://www.linkedin.com/jobs/search/?position=1&pageNum=0" ] }; // Run the Actor and wait for it to finish const run = await client.actor("leadstrategus/apify1-linkedin-job-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 = { "urls": ["https://www.linkedin.com/jobs/search/?position=1&pageNum=0"] } # Run the Actor and wait for it to finish run = client.actor("leadstrategus/apify1-linkedin-job-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 '{ "urls": [ "https://www.linkedin.com/jobs/search/?position=1&pageNum=0" ] }' | apify call leadstrategus/apify1-linkedin-job-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=leadstrategus/apify1-linkedin-job-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Job Scraper", "description": "Extract detailed job data from LinkedIn public job search pages using a simple search URL. Capture titles, company info, locations, full descriptions, and apply links. Supports filters, company insights, and location splitting to bypass result limits. Outputs structured data in JSON, CSV, or Excel", "version": "0.0", "x-build-id": "A6ZGbrSVMKdaRQkak" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/leadstrategus~apify1-linkedin-job-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-leadstrategus-apify1-linkedin-job-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/leadstrategus~apify1-linkedin-job-scraper/runs": { "post": { "operationId": "runs-sync-leadstrategus-apify1-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/leadstrategus~apify1-linkedin-job-scraper/run-sync": { "post": { "operationId": "run-sync-leadstrategus-apify1-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urls" ], "properties": { "urls": { "title": "LinkedIn Search URLs", "type": "array", "description": "Paste one or more LinkedIn Job Search URLs here.", "items": { "type": "string" } }, "count": { "title": "Max Items", "minimum": 1, "type": "integer", "description": "Number of jobs to scrape per search URL.", "default": 100 }, "scrapeCompany": { "title": "Scrape Company Details", "type": "boolean", "description": "If enabled, extracts full company descriptions and employee counts.", "default": true }, "splitByLocation": { "title": "Split by Location", "type": "boolean", "description": "Enable this to bypass the 1000-job LinkedIn limit by splitting searches into smaller areas.", "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 } } } } } } } } } } ```