# Linkedin Job Scraper (`freshdata/linkedin-job-scraper`) Actor Exact LinkedIn job posts base on filters. - **URL**: https://apify.com/freshdata/linkedin-job-scraper.md - **Developed by:** [FreshData](https://apify.com/freshdata) (community) - **Categories:** Lead generation, Social media, Jobs - **Stats:** 198 total users, 157 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $8.00 / 1,000 processing data 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 The **Linkedin Job Scraper** is a powerful tool designed to extract detailed job post data from your filters/criteria — without the need for cookies or login. ### ✨ Features - 👤 **Job Posts Detail Extraction** - 🍪 **No Cookies Required** The scraper works without any LinkedIn login or cookies — simplifying setup and execution. ### 🛠️ How It Works 1. 🔗 **Input** Provide valid values for filters. 2. ▶️ **Run the Scraper** Start the actor to extract rich profile post data in real time — results will be available in Apify's Dataset tab. ### 💰 Pricing 1. Paid users: $0.008/1 request = 1 "processing" events / 1 request ($8/1000 requests). 2. Free users: $0.8/1 request = 100 "processing" events/ 1 request ($800/1000 requests). ### ✨ You may also want to check out my other powerful actors: #### For people: - https://apify.com/freshdata/fresh-linkedin-profile-data - https://apify.com/freshdata/linkedin-open-profile-status - https://apify.com/freshdata/linkedin-open-to-work-status - https://apify.com/freshdata/linkedin-detect-activity-time #### For Sales Navigator searches: - https://apify.com/freshdata/linkedin-sales-navigator-scraper - https://apify.com/freshdata/linkedin-sales-account-scraper #### For companies: - https://apify.com/freshdata/linkedin-company-scraper - https://apify.com/freshdata/linkedin-company-insights-scraper - https://apify.com/freshdata/linkedin-company-by-domain - https://apify.com/freshdata/linkedin-company-custom-headcount #### For jobs: - https://apify.com/freshdata/linkedin-job-details-scraper - https://apify.com/freshdata/linkedin-job-scraper #### For posts: - https://apify.com/freshdata/linkedin-post-scraper - https://apify.com/freshdata/get-post-details - https://apify.com/freshdata/linkedin-company-post-scraper - https://apify.com/freshdata/linkedin-post-comments-scraper - https://apify.com/freshdata/reaction-scraper ### 📥 Input Example ```json { "keywords": "marketing", "geo_code": 92000000, "date_posted": "Any time", "experience_levels": ["Director", "Executive"], "company_ids": [ 1035 ], "title_ids": [1,4,7], "onsite_remotes": ["Remote"], "functions": ["Marketing"], "industries": [1256,24,6], "job_types": ["Part-time", "contract"], "sort_by": "Most relevant", "easy_apply": "false", "under_10_applicants": "false", "start": 0 } ```` ### 📤 Output Example ```json { "data": [ { "company": "Microsoft", "company_linkedin_url": "https://www.linkedin.com/company/microsoft", "company_logo": "https://media.licdn.com/dms/image/v2/C560BAQE88xCsONDULQ/company-logo_200_200/company-logo_200_200/0/1630652622688/microsoft_logo?e=1741219200&v=beta&t=cw0sI898Ll3yxC5LKbB3ACgfrsHN0U88mOtn5U8xAW0", "job_title": "Marketing: MBA Internship Opportunities", "job_url": "https://www.linkedin.com/jobs/view/4052310093", "job_urn": "4052310093", "location": "Redmond, WA", "posted_time": "2024-11-29 10:43:18", "remote": "Hybrid", "salary": "$11.2K/yr - $12.2K/yr" }, { "company": "Microsoft", "company_linkedin_url": "https://www.linkedin.com/company/microsoft", "company_logo": "https://media.licdn.com/dms/image/v2/C560BAQE88xCsONDULQ/company-logo_200_200/company-logo_200_200/0/1630652622688/microsoft_logo?e=1741219200&v=beta&t=cw0sI898Ll3yxC5LKbB3ACgfrsHN0U88mOtn5U8xAW0", "job_title": "Digital Marketing Manager, Email Channel", "job_url": "https://www.linkedin.com/jobs/view/4074167312", "job_urn": "4074167312", "location": "Redmond, WA", "posted_time": "2024-11-11 20:29:38", "remote": "Hybrid", "salary": "$83.4K/yr - $183K/yr" } ], "message": "ok", "total": 495 } ``` # Actor input Schema ## `keywords` (type: `string`): Keywords to search for jobs. ## `geo_code` (type: `integer`): Geographical code for filtering jobs. Learn how to [find a geo\_code](https://i.postimg.cc/mkpbn8hS/geo-code.png). ## `date_posted` (type: `string`): Filter jobs by date posted. Acceptable values include predefined date ranges. ## `experience_levels` (type: `array`): Filter jobs by experience levels. Acceptable values include predefined experience levels. ## `company_ids` (type: `string`): Comma-separated company IDs. Example: 1035,2001,3002. Learn how to [find a company\_id](https://i.postimg.cc/1zVwkP3B/company-id.png). ## `title_ids` (type: `string`): Comma-separated title IDs. Learn how to [find a title\_id](https://i.postimg.cc/sgNhW4c7/title-id.png). ## `industries` (type: `string`): Comma-separated industry names. Learn how to [find an industry\_id here](https://learn.microsoft.com/en-us/linkedin/shared/references/reference-tables/industry-codes-v2). ## `onsite_remotes` (type: `array`): Possible values: ## `functions` (type: `array`): No description ## `job_types` (type: `array`): Possible values: Full-time, Part-time, Contract, Temporary, Internship, Other. ## `sort_by` (type: `string`): Default value: Most relevant. Possible values: Most recent, Most relevant. ## `easy_apply` (type: `string`): No description ## `under_10_applicants` (type: `string`): Filter jobs with less than 10 applicants. Acceptable values are 'true' or 'false'. ## `start` (type: `integer`): Pagination start index. Default: 0 ## Actor input object example ```json { "keywords": "marketing", "geo_code": 92000000, "date_posted": "Any time", "experience_levels": [ "Internship", "Entry level" ], "company_ids": "1035,1053", "onsite_remotes": [ "Remote", "Hybrid" ], "functions": [ "Marketing", "Sales" ], "job_types": [ "Full-time", "Internship" ], "easy_apply": "false", "under_10_applicants": "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 = { "keywords": "marketing", "geo_code": 92000000, "experience_levels": [ "Internship", "Entry level" ], "company_ids": "1035,1053" }; // Run the Actor and wait for it to finish const run = await client.actor("freshdata/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 = { "keywords": "marketing", "geo_code": 92000000, "experience_levels": [ "Internship", "Entry level", ], "company_ids": "1035,1053", } # Run the Actor and wait for it to finish run = client.actor("freshdata/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 '{ "keywords": "marketing", "geo_code": 92000000, "experience_levels": [ "Internship", "Entry level" ], "company_ids": "1035,1053" }' | apify call freshdata/linkedin-job-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=freshdata/linkedin-job-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Job Scraper", "description": "Exact LinkedIn job posts base on filters.", "version": "0.0", "x-build-id": "nJggC81BueX7fZXyg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/freshdata~linkedin-job-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-freshdata-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/freshdata~linkedin-job-scraper/runs": { "post": { "operationId": "runs-sync-freshdata-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/freshdata~linkedin-job-scraper/run-sync": { "post": { "operationId": "run-sync-freshdata-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "keywords": { "title": "keywords", "type": "string", "description": "Keywords to search for jobs." }, "geo_code": { "title": "geo_code", "type": "integer", "description": "Geographical code for filtering jobs. Learn how to [find a geo_code](https://i.postimg.cc/mkpbn8hS/geo-code.png)." }, "date_posted": { "title": "date_posted", "enum": [ "Any time", "Past month", "Past week", "Past 24 hours" ], "type": "string", "description": "Filter jobs by date posted. Acceptable values include predefined date ranges." }, "experience_levels": { "title": "experience_levels", "type": "array", "description": "Filter jobs by experience levels. Acceptable values include predefined experience levels.", "items": { "type": "string", "enum": [ "Internship", "Associate", "Director", "Entry level", "Mid-Senior level", "Executive" ] } }, "company_ids": { "title": "company_ids", "type": "string", "description": "Comma-separated company IDs. Example: 1035,2001,3002. Learn how to [find a company_id](https://i.postimg.cc/1zVwkP3B/company-id.png)." }, "title_ids": { "title": "title_ids", "type": "string", "description": "Comma-separated title IDs. Learn how to [find a title_id](https://i.postimg.cc/sgNhW4c7/title-id.png)." }, "industries": { "title": "industries", "type": "string", "description": "Comma-separated industry names. Learn how to [find an industry_id here](https://learn.microsoft.com/en-us/linkedin/shared/references/reference-tables/industry-codes-v2)." }, "onsite_remotes": { "title": "onsite_remotes", "type": "array", "description": "Possible values: ", "items": { "type": "string", "enum": [ "On-site", "Remote", "Hybrid" ] } }, "functions": { "title": "functions", "type": "array", "description": "", "items": { "type": "string", "enum": [ "Accounting", "Consulting", "Education", "Finance", "Health Care Provider", "Human Resources", "Legal", "Marketing", "Sales", "Business Development", "Other", "Strategy/Planning", "Writing/Editing", "Public Relations", "Information Technology", "Art/Creative", "Administrative", "Advertising", "Engineering", "Project Management", "Production", "Product Management", "Purchasing", "Quality Assurance", "Research", "Customer Service" ] } }, "job_types": { "title": "job_types", "type": "array", "description": "Possible values: Full-time, Part-time, Contract, Temporary, Internship, Other.", "items": { "type": "string", "enum": [ "Full-time", "Part-time", "Contract", "Temporary", "Internship", "Other" ] } }, "sort_by": { "title": "sort_by", "enum": [ "Most recent", "Most relevant" ], "type": "string", "description": "Default value: Most relevant. Possible values: Most recent, Most relevant." }, "easy_apply": { "title": "easy_apply", "enum": [ "true", "false" ], "type": "string", "description": "" }, "under_10_applicants": { "title": "under_10_applicants", "enum": [ "true", "false" ], "type": "string", "description": "Filter jobs with less than 10 applicants. Acceptable values are 'true' or 'false'." }, "start": { "title": "start", "type": "integer", "description": "Pagination start index. Default: 0" } } }, "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 } } } } } } } } } } ```