# LinkedIn Hiring Signals (`schesds/linkedin-hiring-signals`) Actor Monitor hiring activity from LinkedIn company job listings and summarize role, location, seniority, remote-work, and growth signals by company. - **URL**: https://apify.com/schesds/linkedin-hiring-signals.md - **Developed by:** [Tedd Shesden](https://apify.com/schesds) (community) - **Categories:** Jobs, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00 / 1,000 linkedin jobs 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 Hiring Signals Monitor hiring activity from LinkedIn company job listings and turn open roles into company-level signals. This Actor is designed for sales, recruiting, strategy, market intelligence, and investment research teams that want to understand where companies are hiring, which functions are expanding, and whether hiring suggests product, AI, go-to-market, operational, or geographic momentum. ### What You Get For each LinkedIn company input, the Actor analyzes the available job listings and returns one `linkedin_job` row per delivered job. Each job row also includes company-level hiring signals, so you can use the output both as a job dataset and as a company hiring-intelligence dataset. - Job title, job URL, job ID, company, location, published date, seniority, work type, salary, skills, and description when available - Company total jobs delivered in the run - Company jobs posted in the last 30 and 90 days when dates are available - Company hiring signal strength: `LOW`, `MEDIUM`, or `HIGH` - Detected signals such as `AI_OR_DATA_HIRING`, `ENGINEERING_EXPANSION`, `GO_TO_MARKET_EXPANSION`, `REMOTE_FRIENDLY_HIRING`, and `MULTI_LOCATION_HIRING` - Company AI/data, engineering, product, go-to-market, remote, location, and function counts - Clean error rows for inputs that could not be analyzed ### Use Cases - Track hiring momentum across target accounts - Detect companies expanding engineering, AI/data, sales, or operations teams - Monitor competitors' hiring patterns - Build monthly company hiring signal datasets - Enrich CRM, market maps, or research dashboards with hiring activity ### Input Add one or more LinkedIn company IDs or LinkedIn company jobs/search URLs. #### Example ```json { "companyInputs": [ "30898036" ] } ```` You can also use a LinkedIn jobs/search URL: ```json { "companyInputs": [ "https://www.linkedin.com/jobs/search/?f_C=30898036" ] } ``` ### Output The default dataset view is `mapped_jobs`. Each delivered vacancy is emitted as one `linkedin_job` row. Failed inputs produce `scrape_error` rows with `failureStage` and `errorMessage`. Results can be exported from Apify as JSON, CSV, Excel, XML, RSS, or HTML. ### Pricing When pay-per-event monetization is enabled, the Actor charges one event for each delivered `linkedin_job` row. Failed inputs and diagnostic rows are not charged. Company job availability can vary widely. The Actor returns and charges for every delivered job row, so billing stays aligned with the exact number of mapped vacancies delivered to the user. ### Notes - Field coverage depends on what is available for the company's LinkedIn job listings. - This Actor returns mapped job rows enriched with company-level hiring signals. - The first public version focuses on company-level hiring signals from available LinkedIn job listings. More specialized benchmarks, time-series comparisons, and alerting workflows can be added later. # Actor input Schema ## `companyInputs` (type: `array`): Add LinkedIn company IDs or company jobs/search URLs. The Actor analyzes all jobs found for each company input and returns one row per delivered job, enriched with company-level hiring signals. Example company ID: 30898036. Example URL: https://www.linkedin.com/jobs/search/?f\_C=30898036 ## Actor input object example ```json { "companyInputs": [ "30898036" ] } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "companyInputs": [ "30898036" ] }; // Run the Actor and wait for it to finish const run = await client.actor("schesds/linkedin-hiring-signals").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 = { "companyInputs": ["30898036"] } # Run the Actor and wait for it to finish run = client.actor("schesds/linkedin-hiring-signals").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 '{ "companyInputs": [ "30898036" ] }' | apify call schesds/linkedin-hiring-signals --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=schesds/linkedin-hiring-signals", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Hiring Signals", "description": "Monitor hiring activity from LinkedIn company job listings and summarize role, location, seniority, remote-work, and growth signals by company.", "version": "0.1", "x-build-id": "0LYjJJ60hbyambRrO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/schesds~linkedin-hiring-signals/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-schesds-linkedin-hiring-signals", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/schesds~linkedin-hiring-signals/runs": { "post": { "operationId": "runs-sync-schesds-linkedin-hiring-signals", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/schesds~linkedin-hiring-signals/run-sync": { "post": { "operationId": "run-sync-schesds-linkedin-hiring-signals", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companyInputs" ], "properties": { "companyInputs": { "title": "LinkedIn company IDs or jobs URLs", "type": "array", "description": "Add LinkedIn company IDs or company jobs/search URLs. The Actor analyzes all jobs found for each company input and returns one row per delivered job, enriched with company-level hiring signals. Example company ID: 30898036. Example URL: https://www.linkedin.com/jobs/search/?f_C=30898036", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```