# LinkedIn Jobs Scraper Pro (`data_dino/linkedin-jobs-scraper-pro`) Actor Extract 1,000 LinkedIn job listings in ~5 minutes. No login, no cookies, no account risk — just fast, reliable job data from 45+ countries. - **URL**: https://apify.com/data\_dino/linkedin-jobs-scraper-pro.md - **Developed by:** [Data Dino](https://apify.com/data_dino) (community) - **Categories:** Lead generation, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.25 / 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 ## 🔥 LinkedIn Jobs Scraper Extract 1,000 LinkedIn job listings in ~5 minutes. No login, no cookies, no account risk — just fast, reliable job data from 45+ countries. --- ### What Makes It Different - **Zero-cookie, zero-risk.** Most LinkedIn scrapers require cookies or login — putting your account at risk. This one runs entirely on residential proxies with no account needed. Your LinkedIn profile stays safe. - **Adaptive throughput.** Automatically scales scraper concurrency based on available memory. More RAM = more simultaneous scrapers = faster results. At 4 GB, you get ~500 results/minute. - **Full job descriptions + direct apply URLs.** Fetches the complete job listing (not just a preview snippet) along with the employer's own careers page link. No other scraper in this price range gives you both. --- ### Sample Output ```json [ { "title": "Software Engineer, New Grad (AI)", "company": "Notion", "location": "San Francisco, CA", "job_url": "https://www.linkedin.com/jobs/view/4407498584", "id": "li-4407498584", "date_posted": "2026-06-09", "description": "**About The Role**\nAs an engineer at Notion, you'll help shape...", "site": "linkedin", "job_type": "fulltime", "min_amount": null, "max_amount": null, "currency": null, "is_remote": false, "job_level": "entry level", "job_function": "Engineering and Information Technology", "listing_type": null, "emails": null, "company_industry": "Software Development", "company_url": "https://www.linkedin.com/company/notionhq", "company_logo": "https://media.licdn.com/dms/image/v2/D4E0BAQGwvcv_1tHZ4w/company-logo_100_100/...", } ] ```` *** ### Input | Field | Type | Required | Description | Default | |---|---|---|---|---| | `keywords` | string\[] | ✅ | Job titles or keywords to search. Each keyword runs as an independent scrape (e.g. `["software engineer", "data analyst"]`). LinkedIn boolean operators are supported. | — | | `location` | string | — | City, state, or region. Fold country into your location string for best results (e.g. `"London, United Kingdom"`, `"Berlin, Germany"`). | `""` | | `datePosted` | string | — | Only show jobs posted on or after this date in `YYYY-MM-DD` format (e.g. `"2026-06-01"`). Converts automatically to a freshness window. | No filter | | `job_type` | string | — | `fulltime`, `parttime`, `contract`, `temporary`, `internship` | Any | | `is_remote` | boolean | — | Only show remote jobs | `false` | | `maxItems` | integer | — | Maximum results per keyword (1–10,000) | `20` | #### Example Input ```json { "keywords": ["software engineer", "data analyst"], "location": "San Francisco, California", "datePosted": "2026-06-01", "job_type": "fulltime", "is_remote": false, "maxItems": 20 } ``` *** ### Output Each job listing returns a JSON object with the fields below. Fields that depend on employer-provided data (salary, company metadata, skills, etc.) are `null` when not available — only the core identity fields are guaranteed non-null. #### Core Fields | Field | Type | Description | |---|---|---| | `title` | string | Job title | | `company` | string | Company name | | `location` | string | Job location (city, state, or empty) | | `job_url` | string | LinkedIn job listing URL | | `job_url_direct` | string? | Employer's own careers page URL for direct applications | | `id` | string | LinkedIn's persistent job posting ID — stable across runs for deduplication | | `date_posted` | string | ISO date the job was posted (`YYYY-MM-DD`) | | `description` | string | Full job description in markdown format (not a truncated preview) | | `site` | string | Source site (`"linkedin"`) | | `job_type` | string | `fulltime`, `parttime`, `contract`, `temporary`, `internship` | | `is_remote` | boolean | Whether the job is remote | | `job_level` | string | Seniority level (e.g. `"entry level"`, `"mid-senior level"`) | | `job_function` | string | Job function category (e.g. `"Engineering"`, `"Engineering and Information Technology"`) | #### Salary Fields When the employer includes salary information in the listing: | Field | Type | Description | |---|---|---| | `salary_source` | string? | Where the salary data came from (e.g. `"description"` when parsed from the job description) | | `interval` | string? | Pay interval (e.g. `"yearly"`, `"monthly"`, `"hourly"`) | | `min_amount` | number? | Minimum of the posted salary range | | `max_amount` | number? | Maximum of the posted salary range | | `currency` | string? | ISO 4217 currency code (e.g. `"USD"`) | #### Company Fields | Field | Type | Description | |---|---|---| | `company_industry` | string? | Industry classification (e.g. `"Software Development"`, `"Financial Services"`) | | `company_url` | string? | Company's LinkedIn page URL | | `company_logo` | string? | URL of the company's LinkedIn profile image | #### Additional Fields | Field | Type | Description | |---|---|---| | `emails` | string? | Email addresses found in the job description | | `listing_type` | string? | Listing classification (e.g. sponsored, organic) | | `skills` | string? | Skills mentioned or required in the posting | | `experience_range` | string? | Years of experience required | | `vacancy_count` | number? | Number of open positions for this listing | | `work_from_home_type` | string? | Hybrid/remote classification details | *** ### Use Cases - **Job seekers** — Monitor fresh listings in your field across multiple keywords and locations in one run. Filter by recency and job type to focus on what matters. - **Recruiters & staffing agencies** — Build candidate pipeline datasets. Track hiring velocity at target companies. Map the competitive landscape by role and location. - **Market researchers** — Analyse salary trends, skill demand, and hiring volume. Compare job markets across cities and countries. - **Sales & lead generation** — Identify companies that are actively hiring for roles your product serves. Time outreach to match growth signals. *** ### FAQ **Do I need a LinkedIn account?** No. This scraper runs entirely on residential proxies — no login, no cookies, no account required. Your LinkedIn profile is never involved. **Can I scrape multiple keywords at once?** Yes. Submit an array of keywords and each one runs as an independent scrape job. Results are combined into a single dataset, tagged by search term. **What countries are supported?** LinkedIn search covers 45+ countries. Include the country in your `location` string (e.g. `"London, United Kingdom"`) for accurate geo-targeting. # Actor input Schema ## `keywords` (type: `array`): Job titles or keywords to search for (e.g. 'software engineer', 'data analyst') ## `location` (type: `string`): City, state, or region to search in (e.g. 'San Francisco', 'Remote') ## `datePosted` (type: `string`): Filter jobs posted on or after this date (YYYY-MM-DD), or use relative strings like 'week', 'month', '24 hours' ## `job_type` (type: `string`): Type of employment ## `is_remote` (type: `boolean`): Only show remote jobs ## `sites` (type: `string`): Job board to scrape (select one) ## `maxItems` (type: `integer`): Maximum number of job listings to return ## Actor input object example ```json { "keywords": [ "software engineer", "data analyst" ], "location": "San Francisco", "datePosted": "2026-06-02", "job_type": "", "is_remote": false, "sites": "linkedin", "maxItems": 20 } ``` # 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": [ "software engineer", "data analyst" ], "location": "San Francisco", "datePosted": "2026-06-02", "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("data_dino/linkedin-jobs-scraper-pro").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": [ "software engineer", "data analyst", ], "location": "San Francisco", "datePosted": "2026-06-02", "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("data_dino/linkedin-jobs-scraper-pro").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": [ "software engineer", "data analyst" ], "location": "San Francisco", "datePosted": "2026-06-02", "maxItems": 20 }' | apify call data_dino/linkedin-jobs-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_dino/linkedin-jobs-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper Pro", "description": "Extract 1,000 LinkedIn job listings in ~5 minutes. No login, no cookies, no account risk — just fast, reliable job data from 45+ countries.", "version": "1.0", "x-build-id": "SBosA83OvUhnm0Bju" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_dino~linkedin-jobs-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_dino-linkedin-jobs-scraper-pro", "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/data_dino~linkedin-jobs-scraper-pro/runs": { "post": { "operationId": "runs-sync-data_dino-linkedin-jobs-scraper-pro", "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/data_dino~linkedin-jobs-scraper-pro/run-sync": { "post": { "operationId": "run-sync-data_dino-linkedin-jobs-scraper-pro", "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": [ "keywords" ], "properties": { "keywords": { "title": "Search Keywords", "type": "array", "description": "Job titles or keywords to search for (e.g. 'software engineer', 'data analyst')", "items": { "type": "string" } }, "location": { "title": "Location", "type": "string", "description": "City, state, or region to search in (e.g. 'San Francisco', 'Remote')" }, "datePosted": { "title": "Date Posted", "type": "string", "description": "Filter jobs posted on or after this date (YYYY-MM-DD), or use relative strings like 'week', 'month', '24 hours'" }, "job_type": { "title": "Job Type", "enum": [ "", "fulltime", "parttime", "contract", "internship", "temporary" ], "type": "string", "description": "Type of employment", "default": "" }, "is_remote": { "title": "Remote Only", "type": "boolean", "description": "Only show remote jobs", "default": false }, "sites": { "title": "Job Site", "enum": [ "linkedin" ], "type": "string", "description": "Job board to scrape (select one)", "default": "linkedin" }, "maxItems": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of job listings to return", "default": 20 } } }, "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 } } } } } } } } } } ```