# Wellfound Jobs Scraper (Cheap) (`data_api/wellfound-jobs-scraper-cheap`) Actor Extract startup job listings and company data from Wellfound across any role or city search, giving you salary ranges, remote policies, funding badges, and experience requirements for every listing. - **URL**: https://apify.com/data\_api/wellfound-jobs-scraper-cheap.md - **Developed by:** [Data API](https://apify.com/data_api) (community) - **Categories:** Jobs, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 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 ## Wellfound Jobs Scraper ![Wellfound Jobs Scraper](cover.jpg) Wellfound is where startups list their open roles, but the site gives you no easy way to pull those listings into a sheet. You end up tabbing through results, copying titles and salaries by hand, and losing track of which company posted what. This scraper does the collecting for you. Give it a role, a city, or a company handle and every Wellfound posting comes back as a clean row, with the title, pay range, location, company, and posting date already split into columns. Run one search or stack dozens, and only pay for the listings you actually pull. ### What you get Every posting comes back as one row with a steady set of columns, so loading the data into a spreadsheet or database is predictable. The fields fall into two groups: - **Job details** — `roleName`, `employmentType`, `roleCategory`, `salaryRange`, `officeLocations`, `remoteFriendly`, `remoteRegions`, `minYearsExperience`, `maxYearsExperience`, `publishedAt`, `roleSummary`, `postingUrl`, `postingId` - **Company details** — `employerName`, `employerHandle`, `headcountBand`, `employerTagline`, `employerTags`, `employerLogo`, `employerId`, plus the `queryLabel` that surfaced the row and a `collectedAt` timestamp ### Quick start 1. Hit **Try for free** to open the input form. 2. Add role slugs under **Role keywords** (such as `backend-engineer`), cities under **Cities or regions**, or company handles under **Company handles** — any one of the three is enough. 3. Set **Listings cap per search** and **Page depth per search** to control how much you pull. 4. Press **Start**, then export the results as JSON, CSV, Excel, or XML once the run finishes. ![How it works](how-it-works.jpg) ### Use cases - **Recruiting and sourcing** — track which startups are hiring for a role and reach out before the post goes stale - **Job seekers** — pull every opening for your role across cities into one list you can sort and filter - **Salary benchmarking** — gather advertised pay ranges by role and company size to see where you stand - **Startup and market research** — map hiring activity to spot which companies and sectors are growing - **Talent intelligence** — build a feed of a competitor's open roles to read their roadmap and headcount plans ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `jobRoles` | array of strings | One of `jobRoles`, `searchLocations`, or `employerHandles` | Role slugs in Wellfound's hyphenated URL form, e.g. `backend-engineer`. Each role is searched on its own. | | `searchLocations` | array of strings | One of `jobRoles`, `searchLocations`, or `employerHandles` | City or region slugs such as `berlin`, `london`, or `remote`. Each is paired with every role you list. | | `employerHandles` | array of strings | One of `jobRoles`, `searchLocations`, or `employerHandles` | Company handles such as `figma` or `ramp` to pull openings straight from named companies. | | `resultsPerQuery` | integer | No | Most listings to collect per search. Total run output is this value times the number of searches. Default `30`. | | `pageLimit` | integer | No | How deep to page through each search; a page holds 20 to 40 listings. Default `2`. | | `timeoutSeconds` | integer | No | Seconds to wait on a single request before giving up. Default `75`. | #### Example input ```json { "jobRoles": ["backend-engineer", "growth-marketer"], "searchLocations": ["berlin", "london"], "employerHandles": ["figma", "ramp"], "resultsPerQuery": 30, "pageLimit": 2, "timeoutSeconds": 75 } ```` ### Output Each posting becomes one row, and the columns stay consistent across the whole run so your dataset loads cleanly into any tool. #### Example output ```json { "postingId": "1289473", "roleName": "Senior Backend Engineer", "employmentType": "full-time", "roleCategory": "Software Engineer", "postingUrl": "https://wellfound.com/company/lumina-labs/jobs/1289473", "roleSummary": "Own and scale the services that power our payments platform, working closely with product and design.", "salaryRange": "$140k – $180k", "officeLocations": ["Berlin", "Remote (EU)"], "remoteFriendly": true, "remoteRegions": ["Europe"], "minYearsExperience": 4, "maxYearsExperience": 8, "publishedAt": "2026-06-21T09:15:00Z", "autoListed": false, "employerId": "57210", "employerName": "Lumina Labs", "employerHandle": "lumina-labs", "headcountBand": "51-200", "employerLogo": "https://photos.wellfound.com/startups/i/57210-logo.png", "employerTagline": "Payments infrastructure for modern fintech teams", "employerTags": ["Actively Hiring", "Series B"], "queryLabel": "backend-engineer / berlin", "collectedAt": "2026-06-30T12:00:00.000000+00:00" } ``` #### Output fields | Field | Type | Description | |-------|------|-------------| | `postingId` | string | Wellfound's identifier for the job posting | | `roleName` | string | Job title as shown on the posting | | `employmentType` | string | How the role is offered, e.g. full-time, contract, internship | | `roleCategory` | string | Broad function the role sits under, such as Software Engineer | | `postingUrl` | string | Direct link to the posting on Wellfound | | `roleSummary` | string | Description text for the role, when present | | `salaryRange` | string | Advertised pay band, when the company publishes it | | `officeLocations` | array | Places where the role is based | | `remoteFriendly` | boolean | True when the posting allows remote work | | `remoteRegions` | array | Regions a remote hire may work from | | `minYearsExperience` | integer | Lowest experience level requested | | `maxYearsExperience` | integer | Upper experience level mentioned | | `publishedAt` | string | When the posting first went live | | `autoListed` | boolean | True when Wellfound posted the role automatically | | `employerId` | string | Wellfound identifier for the hiring company | | `employerName` | string | Name of the company that is hiring | | `employerHandle` | string | Company handle used in its Wellfound profile URL | | `headcountBand` | string | Rough company size bracket, e.g. 51-200 | | `employerLogo` | string | URL of the company logo image | | `employerTagline` | string | One-line pitch describing what the company does | | `employerTags` | array | Badge labels on the company profile, such as Actively Hiring | | `queryLabel` | string | The search that surfaced this row | | `collectedAt` | string | ISO 8601 timestamp of when the row was captured | ### Tips for best results - **Use the slug, not the label.** Roles and cities have to match Wellfound's URL form — `product-manager`, not `Product Manager`. Open a search on the site and copy the slug from the address bar. - **Watch your totals.** Output is `resultsPerQuery` multiplied by the number of searches, so a few roles across a few cities adds up fast. Start with a small cap while you check the shape of the data. - **Mix the three inputs.** Roles and cities cross-multiply, while each company handle runs as its own search. You can combine all three in one run. - **Some fields come back empty.** Not every company publishes a salary or a description, so `salaryRange` and `roleSummary` can be `null` — that is the listing, not a scraper fault. - **Raise `timeoutSeconds`** if you see repeated request failures on a slow connection. ### How can I use Wellfound jobs data? **How can I use the Wellfound Jobs Scraper to track startup hiring?** Add the company handles you follow under `employerHandles` and run the scraper on a schedule. Each row carries the role, pay range, location, and posting date, so a fresh export tells you what every company is hiring for and how their headcount plans are shifting over time. **How can I export Wellfound job listings to a spreadsheet?** Run a search by role or city, then download the dataset as CSV or Excel when it finishes. Every posting is already split into columns — title, salary, company, location — so you can sort, filter, and pivot the Wellfound data without any cleanup. **How can I benchmark startup salaries with Wellfound data?** List the roles you care about under `jobRoles`, add a few cities, and collect the postings. Group the `salaryRange` and `headcountBand` fields by role to compare advertised pay across company sizes and locations — a quick read on where a given role sits in the market. **How can I find remote startup jobs on Wellfound?** Add `remote` as a location slug or scan the `remoteFriendly` and `remoteRegions` fields in the output. Filter the rows to remote-eligible postings and you have a focused list of startup roles you can work from anywhere they allow. ### Is it legal to scrape data? Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. You can also read Apify's blog post on the [legality of web scraping](https://blog.apify.com/is-web-scraping-legal/). ### Support Questions, feature requests, or a field you'd like added? Reach out at and we'll get back to you. # Actor input Schema ## `jobRoles` (type: `array`): Roles to look up, written as the hyphenated slug Wellfound uses in its URLs, for example backend-engineer, growth-marketer, ux-designer. Every role is searched on its own. ## `searchLocations` (type: `array`): Cities or regions to target, written as slugs such as berlin, london, boston, or remote. Each one is paired with every role you list. ## `employerHandles` (type: `array`): Pull openings straight from named companies using their Wellfound handle, for example figma, ramp, vercel. Each handle is searched separately. ## `resultsPerQuery` (type: `integer`): The most listings to gather for each individual search. With 3 roles across 2 cities you get 6 searches, so the run total is 6 times this number. ## `pageLimit` (type: `integer`): How deep to page through each search. A single page holds somewhere between 20 and 40 listings. ## `timeoutSeconds` (type: `integer`): How long to wait on a single request before giving up. Bump it up when your connection is slow. ## Actor input object example ```json { "jobRoles": [ "backend-engineer", "growth-marketer" ], "searchLocations": [ "berlin", "london" ], "employerHandles": [ "figma", "ramp" ], "resultsPerQuery": 25, "pageLimit": 2, "timeoutSeconds": 75 } ``` # 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 = { "jobRoles": [ "backend-engineer" ], "searchLocations": [ "berlin" ] }; // Run the Actor and wait for it to finish const run = await client.actor("data_api/wellfound-jobs-scraper-cheap").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 = { "jobRoles": ["backend-engineer"], "searchLocations": ["berlin"], } # Run the Actor and wait for it to finish run = client.actor("data_api/wellfound-jobs-scraper-cheap").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 '{ "jobRoles": [ "backend-engineer" ], "searchLocations": [ "berlin" ] }' | apify call data_api/wellfound-jobs-scraper-cheap --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_api/wellfound-jobs-scraper-cheap", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wellfound Jobs Scraper (Cheap)", "description": "Extract startup job listings and company data from Wellfound across any role or city search, giving you salary ranges, remote policies, funding badges, and experience requirements for every listing.", "version": "0.0", "x-build-id": "xIWP9HthpHEq3FGhQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_api~wellfound-jobs-scraper-cheap/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_api-wellfound-jobs-scraper-cheap", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_api~wellfound-jobs-scraper-cheap/runs": { "post": { "operationId": "runs-sync-data_api-wellfound-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_api~wellfound-jobs-scraper-cheap/run-sync": { "post": { "operationId": "run-sync-data_api-wellfound-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "jobRoles": { "title": "Role keywords", "type": "array", "description": "Roles to look up, written as the hyphenated slug Wellfound uses in its URLs, for example backend-engineer, growth-marketer, ux-designer. Every role is searched on its own.", "items": { "type": "string" } }, "searchLocations": { "title": "Cities or regions", "type": "array", "description": "Cities or regions to target, written as slugs such as berlin, london, boston, or remote. Each one is paired with every role you list.", "items": { "type": "string" } }, "employerHandles": { "title": "Company handles", "type": "array", "description": "Pull openings straight from named companies using their Wellfound handle, for example figma, ramp, vercel. Each handle is searched separately.", "items": { "type": "string" } }, "resultsPerQuery": { "title": "Listings cap per search", "minimum": 1, "maximum": 500, "type": "integer", "description": "The most listings to gather for each individual search. With 3 roles across 2 cities you get 6 searches, so the run total is 6 times this number.", "default": 25 }, "pageLimit": { "title": "Page depth per search", "minimum": 1, "maximum": 20, "type": "integer", "description": "How deep to page through each search. A single page holds somewhere between 20 and 40 listings.", "default": 2 }, "timeoutSeconds": { "title": "Timeout (seconds)", "minimum": 10, "maximum": 120, "type": "integer", "description": "How long to wait on a single request before giving up. Bump it up when your connection is slow.", "default": 75 } } }, "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 } } } } } } } } } } ```