# Theladders Jobs Search Scraper (`stealth_mode/theladders-jobs-search-scraper`) Actor Scrape structured job listings from TheLadders.com including salary bands, remote flags, company info, and location data. Perfect for recruiters, job aggregators, and compensation analysts targeting the $100K+ job market. - **URL**: https://apify.com/stealth\_mode/theladders-jobs-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## TheLadders.com Jobs Scraper: Extract High-Salary Job Listings at Scale --- ### What Is TheLadders.com? TheLadders.com is a premium job platform focused on high-salary professional roles, typically targeting positions in the $100,000+ range. It serves executives, senior engineers, finance professionals, and other experienced candidates across industries. Because listings are curated for high-value roles, the data found here — particularly compensation bands and seniority signals — is especially valuable for market research and talent intelligence work. Manually collecting this data across hundreds of search pages is impractical. The **TheLadders.com Jobs Scraper** automates extraction from search result pages, returning clean, structured records for each listing. --- ### Overview The **TheLadders Jobs Scraper** targets job search result pages and extracts up to 28 fields per listing. It is suited for: - **Recruiters** monitoring the premium job market by industry or location - **Compensation analysts** benchmarking salary bands across roles - **Job board developers** aggregating high-salary listings - **HR researchers** studying remote work trends and hiring patterns in senior roles --- ### Input Format ```json { "urls": [ "https://www.theladders.com/jobs/engineering-construction-jobs?sort=ByRelevance&page=2" ], "ignore_url_failures": true, "max_items_per_url": 50 } ```` | Field | Type | Description | |---|---|---| | `urls` | `array` | One or more TheLadders job search result page URLs. Supports bulk entry. Example: filter by category, keyword, or sort order via URL parameters. | | `max_items_per_url` | `integer` | Maximum number of job records to collect per URL. Default: `20`. Increase to `50`+ for larger runs. | | `ignore_url_failures` | `boolean` | If `true`, the scraper skips failed URLs and continues instead of stopping the entire run. Recommended for bulk URL lists. | > **Tip:** Use TheLadders' built-in filters (industry, location, remote) in the URL before passing it to the scraper to pre-segment your dataset. *** ### Output Format **Sample output** ```json { "job_location_id": { "id": "86967919", "numeric_id": 86967919 }, "job_status": "Approved", "promoted_label_visible": false, "company_name": "Appcast", "county": "MARION", "years_experience": "5 - 7", "posting_date": "May 19, 2026, 1:59:03 AM", "title": "Roadway Engineer II", "promoted": false, "lower_band": 74800, "candidate_residency": [], "compensation_bonus": "", "industry_id": 2022, "posted_dates": [ { "posting_date": "May 19, 2026, 1:59:03 AM" } ], "remote_flag": "In-Person", "industry_name": "Transportation", "is_ladders_estimate": false, "compensation_other": "", "active": true, "recruiter_anonymous": false, "short_description": "Empower your career by leading roadway engineering projects, from design to implementation, ensuring quality deliverables. Collaborate with diverse teams and mentor emerging professionals while driving innovative infrastructure solutions.", "allow_external_apply": true, "salary_is_confidential": false, "zipcode": "46227", "external_application_url": "https://parsons.wd5.myworkdayjobs.com/Search/job/US---IN-Indianapolis/Roadway-Engineer-II_R180083-1", "upper_band": 130900, "location": "Indianapolis, IN", "locations": [ { "id": "86967919", "text": "Indianapolis, IN", "seo_slug": "roadway-engineer-ii-appcast-indianapolis-in_86967919", "active": true, "coords": { "latitude": 39.6791, "longitude": -86.1278 }, "zipcode": "46227", "brokers": [] } ] } ``` Each job listing returns up to 28 structured fields: #### Identification & Listing Metadata | Field | Meaning | |---|---| | `Job Location ID` | Internal identifier linking the job to a specific location record | | `Job Status` | Current status of the listing (e.g., active, filled) | | `Active` | Boolean flag indicating whether the listing is currently live | | `Posting Date` | Date the job was first published | | `Posted Dates` | Full date range object, may include creation and update timestamps | | `Promoted` | Whether the listing is a paid promoted placement | | `Promoted Label Visible` | Whether the "Promoted" label is shown to candidates on the listing | #### Job Details | Field | Meaning | |---|---| | `Title` | Job title as displayed on TheLadders | | `Short Description` | Brief summary or snippet of the job description | | `Years Experience` | Minimum years of experience required for the role | | `Industry ID` | Internal identifier for the job's industry category | | `Industry Name` | Human-readable industry label (e.g., Engineering, Finance) | | `Remote Flag` | Indicates whether the role is fully remote, hybrid, or on-site | #### Company & Recruiter | Field | Meaning | |---|---| | `Company Name` | Name of the hiring company | | `Recruiter Anonymous` | If `true`, the employer has chosen to remain anonymous | #### Compensation | Field | Meaning | |---|---| | `Lower Band` | Minimum salary figure for the role | | `Upper Band` | Maximum salary figure for the role | | `Is Ladders Estimate` | If `true`, salary is estimated by TheLadders, not provided by the employer | | `Salary Is Confidential` | Employer has explicitly marked salary as confidential | | `Compensation Bonus` | Bonus or incentive compensation details, if available | | `Compensation Other` | Other compensation components (e.g., equity, benefits notes) | #### Location | Field | Meaning | |---|---| | `Location` | Primary job location as a formatted string | | `Locations` | Full location object(s), may include multiple sites | | `Zipcode` | ZIP code associated with the primary job location | | `County` | County or sub-regional area of the listing | | `Candidate Residency` | Any residency requirements specified by the employer | #### Application | Field | Meaning | |---|---| | `Allow External Apply` | Whether candidates can apply via an external URL | | `External Application URL` | Direct link to the employer's own application page, if external | *** ### How to Use 1. **Build your search URL** — Run a search on TheLadders.com with your desired filters (job category, location, remote, sort order). Copy the full URL from your browser. 2. **Configure the input** — Paste one or more URLs into the `urls` array. 3. **Set item limits** — Adjust `max_items_per_url` based on how many results you need. TheLadders typically paginates at ~25 results per page, so combine multiple page URLs for larger datasets. 4. **Run and export** — Start the scraper and download results as JSON, CSV, or Excel. **Best practices:** - Paginate manually by incrementing the `page=` parameter across multiple URLs for full category coverage. - Use `ignore_url_failures: true` whenever running batches to avoid interruptions from occasional 404s or empty pages. - Cross-reference `Is Ladders Estimate` when using salary data for research — estimated figures may differ from employer-reported ranges. *** ### Use Cases & Business Value - **Salary benchmarking:** Collect `Lower Band` / `Upper Band` data across industries to build compensation reports - **Remote work analysis:** Filter by `Remote Flag` to map remote hiring trends in senior roles - **Recruiter intelligence:** Track which companies are hiring anonymously or promoting listings heavily - **Job aggregation:** Feed structured TheLadders listings into internal portals or BI dashboards *** ### Conclusion The **TheLadders.com Jobs Scraper** provides reliable, structured access to one of the most concentrated sources of senior-level job data available online. With compensation fields, remote indicators, and company metadata all captured in a single run, it delivers immediate value for anyone working in talent intelligence, HR analytics, or job market research. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://www.theladders.com/jobs/engineering-construction-jobs?sort=ByRelevance&page=2" ], "ignore_url_failures": true, "max_items_per_url": 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 = { "urls": [ "https://www.theladders.com/jobs/engineering-construction-jobs?sort=ByRelevance&page=2" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/theladders-jobs-search-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.theladders.com/jobs/engineering-construction-jobs?sort=ByRelevance&page=2"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/theladders-jobs-search-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.theladders.com/jobs/engineering-construction-jobs?sort=ByRelevance&page=2" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/theladders-jobs-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/theladders-jobs-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Theladders Jobs Search Scraper", "description": "Scrape structured job listings from TheLadders.com including salary bands, remote flags, company info, and location data. Perfect for recruiters, job aggregators, and compensation analysts targeting the $100K+ job market.", "version": "0.0", "x-build-id": "0c5V0fhOcHgnYA78N" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~theladders-jobs-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-theladders-jobs-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/stealth_mode~theladders-jobs-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-theladders-jobs-search-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/stealth_mode~theladders-jobs-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-theladders-jobs-search-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": { "urls": { "title": "URLs of the Jobs list urls to scrape", "type": "array", "description": "Add the URLs of the Jobs list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```