# LinkedIn Job Scraper — Find Jobs in English (`shayan.nazari/my-actor-1`) Actor Scrape LinkedIn jobs in your language. Find English jobs anywhere in Europe or worldwide. Filters out postings in other languages. Supports 15 languages. Results appear live — download as Excel or JSON when done. - **URL**: https://apify.com/shayan.nazari/my-actor-1.md - **Developed by:** [Shayan nazari](https://apify.com/shayan.nazari) (community) - **Categories:** Jobs - **Stats:** 8 total users, 1 monthly users, 83.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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 Job Scraper Scrape LinkedIn job listings by job title, location, and language. Tell the scraper how many jobs you want in your chosen language — it keeps scraping until it finds that many, or until LinkedIn runs out of results. --- ### How it works 1. Enter your job title, country, and optional city 2. Choose your preferred language (e.g. English) 3. Enter how many matching jobs you want (e.g. 100) 4. The scraper keeps paginating LinkedIn until it has saved that many jobs in your language 5. If LinkedIn runs out of results before reaching your target, it stops automatically 6. Results appear live in the Dataset tab as they are found 7. Download as Excel or JSON when done --- ### Pricing **$10 per 1,000 results.** You are only charged for jobs actually saved — not for pages scanned or jobs filtered out. --- ### Input fields | Field | Description | |---|---| | Job Title | What to search for on LinkedIn. One search at a time. Example: Electrical Engineer | | Country | Country to search in. Example: Italy, Germany | | City | Optional — narrows search to a specific city | | Language | Only save jobs written in this language | | Experience Level | Filter by seniority level | | Date Posted | Any time / Past month / Past week / Past 24 hours | | How many jobs do you want? | Target number of saved jobs in your chosen language. Scraper keeps going until reached or LinkedIn runs out. | | Fetch Full Descriptions | Enables language detection — recommended on | --- ### Output Every saved job includes: | Field | Description | |---|---| | Title | Job title | | Company | Hiring company name | | Location | City and country | | Posted | How long ago the job was posted | | Language | Detected language of the posting | | URL | Link to the LinkedIn job page | | Apply | Clickable link to apply | | Description | Full job description text | Results are available as: - **Live table** in the Dataset tab while running - **Excel file** (.xlsx) in the Storage tab when done - **JSON file** in the Storage tab when done --- ### Tips - Set language to **English** to find English-speaking jobs anywhere in Europe - Use **"Any time"** for date posted to get maximum results - The scraper scans all languages but only saves your chosen one — so it may scan many pages to reach your target in a non-dominant language # Actor input Schema ## `jobTitles` (type: `string`): Enter one job title to search for. You can only search one title at a time. Examples: Electrical Engineer, Software Developer, Data Analyst. ## `country` (type: `string`): Country to search jobs in. Examples: Italy, Germany, Netherlands, United States. ## `city` (type: `string`): Specific city to narrow the search. Leave empty to search the whole country. ## `language` (type: `string`): Only return job postings written in this language. ## `experienceLevel` (type: `string`): Filter jobs by required experience level. ## `datePosted` (type: `string`): Filter jobs by how recently they were posted. ## `maxJobs` (type: `integer`): Number of jobs you want saved in your chosen language. The scraper keeps going until it finds this many matching jobs or LinkedIn runs out of results. Example: enter 100 to get 100 English jobs — the scraper will scan as many pages as needed to find them. ## `fetchDescriptions` (type: `boolean`): Visit each job page to extract the full description and detect language. Disable for faster results. ## Actor input object example ```json { "jobTitles": "Computer Engineer", "country": "Germany", "city": "", "language": "en", "experienceLevel": "", "datePosted": "r604800", "maxJobs": 100, "fetchDescriptions": true } ```` # Actor output Schema ## `results` (type: `string`): Live job results available in the Dataset tab while the Actor is running. Each item contains job\_title, company, description, location, date\_posted, url, and language. ## `excel` (type: `string`): All results as a formatted Excel spreadsheet (.xlsx). ## `json` (type: `string`): All results as a JSON file with metadata (total\_saved, search\_query, location, language, jobs array). # 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("shayan.nazari/my-actor-1").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 = {} # Run the Actor and wait for it to finish run = client.actor("shayan.nazari/my-actor-1").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 '{}' | apify call shayan.nazari/my-actor-1 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shayan.nazari/my-actor-1", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Job Scraper — Find Jobs in English", "description": "Scrape LinkedIn jobs in your language. Find English jobs anywhere in Europe or worldwide. Filters out postings in other languages. Supports 15 languages. Results appear live — download as Excel or JSON when done.", "version": "0.0", "x-build-id": "4TnSFjv83fziOc3Vc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shayan.nazari~my-actor-1/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shayan.nazari-my-actor-1", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/shayan.nazari~my-actor-1/runs": { "post": { "operationId": "runs-sync-shayan.nazari-my-actor-1", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/shayan.nazari~my-actor-1/run-sync": { "post": { "operationId": "run-sync-shayan.nazari-my-actor-1", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "jobTitles", "country", "language", "experienceLevel", "datePosted", "maxJobs", "fetchDescriptions" ], "properties": { "jobTitles": { "title": "Job Title (one search at a time)", "type": "string", "description": "Enter one job title to search for. You can only search one title at a time. Examples: Electrical Engineer, Software Developer, Data Analyst.", "default": "Computer Engineer" }, "country": { "title": "Country", "type": "string", "description": "Country to search jobs in. Examples: Italy, Germany, Netherlands, United States.", "default": "Germany" }, "city": { "title": "City (optional)", "type": "string", "description": "Specific city to narrow the search. Leave empty to search the whole country.", "default": "" }, "language": { "title": "Job Posting Language", "enum": [ "en", "nl", "de", "fr", "es", "it", "pt", "pl", "sv", "da", "no", "fi", "ar", "tr", "ro" ], "type": "string", "description": "Only return job postings written in this language.", "default": "en" }, "experienceLevel": { "title": "Experience Level", "enum": [ "", "1", "2", "3", "4", "5", "6" ], "type": "string", "description": "Filter jobs by required experience level.", "default": "" }, "datePosted": { "title": "Date Posted", "enum": [ "", "r2592000", "r604800", "r86400" ], "type": "string", "description": "Filter jobs by how recently they were posted.", "default": "r604800" }, "maxJobs": { "title": "How many jobs do you want?", "minimum": 25, "maximum": 10000, "type": "integer", "description": "Number of jobs you want saved in your chosen language. The scraper keeps going until it finds this many matching jobs or LinkedIn runs out of results. Example: enter 100 to get 100 English jobs — the scraper will scan as many pages as needed to find them.", "default": 100 }, "fetchDescriptions": { "title": "Fetch Full Job Descriptions", "type": "boolean", "description": "Visit each job page to extract the full description and detect language. Disable for faster results.", "default": true } } }, "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 } } } } } } } } } } ```