# ZipRecruiter Jobs Scraper (Cheap) (`data_api/ziprecruiter-jobs-scraper-cheap`) Actor ZipRecruiter Jobs Scraper collects job listings by keyword and location. You get titles, salaries, company names, and descriptions in a clean dataset, ready to use. - **URL**: https://apify.com/data\_api/ziprecruiter-jobs-scraper-cheap.md - **Developed by:** [Data API](https://apify.com/data_api) (community) - **Categories:** Jobs, Automation, Developer tools - **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 ## ZipRecruiter Jobs Scraper ![ZipRecruiter Jobs Scraper](cover.jpg) Tracking hiring on ZipRecruiter by hand gets old fast. You run the same searches, copy out pay ranges by hand, and half the time a posting is gone before you note it down. This scraper handles that part. Give it the roles and places you care about, and it hands back every matching posting as a tidy row: role title, employer, pay range, location, a direct link, and more. Turn on full details and it also opens each posting for the complete description, posted date, and work type. Run one search or a few hundred in a single pass. ### What you get Every posting comes back as one flat row, so the results drop straight into a sheet or database. Fields that ZipRecruiter doesn't show arrive as `null` rather than going missing, which keeps your columns lined up. Three groups of data per job: - **The role** — `roleTitle`, `employerName`, `jobLocation`, `remoteFriendly`, `quickApply`, `workType` - **Pay** — `payRange` (raw text) plus parsed `payMin`, `payMax`, and `payPeriod` - **Links and detail** — `listingUrl`, `listingId`, `employerUrl`, `roleDescription`, `postedDate`, and the `searchTermUsed` / `searchLocationUsed` that produced each row ### Quick start 1. Hit **Try for free** and open the input form. 2. Add your roles and keywords under **Job search terms**, one per line. 3. Add any cities and states under **Search locations**, or leave it blank to sweep nationwide and remote roles. 4. Turn on **Pull full posting details** if you want the complete description and posted date, set a **Results limit**, then press **Start**. 5. Export the dataset as JSON, CSV, Excel, or XML when the run finishes. ![How it works](how-it-works.jpg) ### Use cases - **Salary benchmarking** — pull live pay ranges for a role across dozens of real postings instead of relying on aggregate averages - **Recruiting research** — see how rival employers word their openings and what they pay before you write your own - **Job board feeds** — pipe fresh listings into your own app, spreadsheet, or database on a schedule - **Resume targeting** — gather a stack of postings for one role and spot the requirements that keep showing up - **Labor market analysis** — track which roles, employers, and locations are hiring over time ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `jobSearchTerms` | array of strings | Yes | Roles, skills, or keywords to look up. Each line runs its own search. | | `searchLocations` | array of strings | No | Cities and states to cover; blank means a nationwide and remote sweep. Each location pairs with every term. | | `includeFullDetails` | boolean | No | Open each posting for the full description, posted date, and work type. Adds one request per job. Default `false`. | | `resultsLimit` | integer | No | Cap on total postings gathered across all terms and places. Default `50`; up to 1000. | | `timeoutSeconds` | integer | No | Seconds to wait on a single request before giving up. Default `90`. | #### Example input ```json { "jobSearchTerms": ["customer success manager", "warehouse associate", "react developer"], "searchLocations": ["Chicago, IL", "Seattle, WA", "Remote"], "includeFullDetails": true, "resultsLimit": 50, "timeoutSeconds": 90 } ```` ### Output Each posting becomes one row, and every field is always present — values ZipRecruiter doesn't publish come back as `null` so the dataset stays rectangular. #### Example output ```json { "searchTermUsed": "react developer", "searchLocationUsed": "Seattle, WA", "roleTitle": "Senior React Developer", "employerName": "Northpoint Software", "jobLocation": "Seattle, WA", "remoteFriendly": true, "payRange": "$120K - $155K/yr", "payMin": 120000, "payMax": 155000, "payPeriod": "YEAR", "quickApply": true, "listingUrl": "https://www.ziprecruiter.com/c/Northpoint-Software/Job/Senior-React-Developer/-in-Seattle,WA?jid=9f2a71c4", "listingId": "9f2a71c4", "employerUrl": "https://www.ziprecruiter.com/co/Northpoint-Software/Jobs", "roleDescription": "We're hiring a Senior React Developer to lead front-end work on our customer platform...", "postedDate": "2026-06-22", "workType": "FULL_TIME", "collectedAt": "2026-06-30T09:15:00+00:00" } ``` #### Output fields | Field | Type | Description | |-------|------|-------------| | `searchTermUsed` | string | The keyword or role title that surfaced this listing | | `searchLocationUsed` | string | The place value passed to this search; blank means nationwide | | `roleTitle` | string | Headline of the advertised position | | `employerName` | string | Company that posted the opening | | `jobLocation` | string | City and state attached to the posting | | `remoteFriendly` | boolean | True when the post is tagged remote or hybrid | | `payRange` | string | Salary line exactly as printed, e.g. $40 - $75/hr | | `payMin` | number | Lower salary figure parsed from the pay line | | `payMax` | number | Upper salary figure parsed from the pay line | | `payPeriod` | string | How pay is quoted: HOUR, YEAR, MONTH, or WEEK | | `quickApply` | boolean | True when a one-click apply button is offered | | `listingUrl` | string | Direct link to the posting on ZipRecruiter | | `listingId` | string | ZipRecruiter's own job identifier from the link | | `employerUrl` | string | Link to the company's ZipRecruiter profile | | `roleDescription` | string | Full plain-text role write-up (only with full details on) | | `postedDate` | string | ISO date the post went live (only with full details on) | | `workType` | string | Arrangement such as FULL\_TIME (only with full details on) | | `collectedAt` | string | ISO timestamp marking when the row was captured | ### Tips for best results - **Start small.** Run a handful of terms before launching a big batch — search format and pairing issues show up fast in the first few rows. - **Skip full details for speed.** With **Pull full posting details** off, the scraper reads roughly 20 postings per page request. Turn it on only when you actually need the description, posted date, and work type, since it costs an extra request per job. - **Cap your spend with `resultsLimit`.** Keep it low while you confirm the output fits your pipeline, then raise it for the full pull. - **Empty pay fields are normal.** ZipRecruiter shows salary only when the employer lists it, so `payMin`, `payMax`, and `payPeriod` come back `null` on many postings. - **Raise `timeoutSeconds`** if you see frequent timeout errors on slower proxy tiers. ### How can I use ZipRecruiter jobs data? **How can I use the ZipRecruiter Jobs Scraper to benchmark salaries for a role?** List the role under **Job search terms**, add the places you want under **Search locations**, and run the scraper. Each posting returns `payRange` along with parsed `payMin`, `payMax`, and `payPeriod`, so you can pull live pay figures from real openings rather than leaning on aggregate averages. Group the rows by location to see how pay shifts from one market to the next. **How can I export ZipRecruiter job listings to a spreadsheet?** Run the scraper with your terms and locations, then export the dataset as CSV or Excel when it finishes. Every posting is one flat row with the role, employer, location, pay, and a direct link, so it opens cleanly in any spreadsheet tool — no cleanup or reformatting needed. **How can I collect full ZipRecruiter job descriptions in bulk?** Turn on **Pull full posting details** before you start. The scraper then opens each posting and adds `roleDescription`, `postedDate`, and `workType` to every row. It's the right setting for resume targeting or recruiting research, where the wording of the description matters as much as the headline. **How can I monitor hiring trends on ZipRecruiter over time?** Schedule the scraper to run on a fixed cadence with the same terms and locations. Because each row carries `collectedAt`, `searchTermUsed`, and `searchLocationUsed`, you can stack runs over weeks and watch which roles, employers, and markets are actively hiring. ### 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 ## `jobSearchTerms` (type: `array`): Roles, skills, or keywords to look up — one per line. Each line triggers its own search. ## `searchLocations` (type: `array`): Cities and states to cover, such as 'Denver, CO'. Leave it blank for a nationwide or remote sweep. Every location is paired with every search term. ## `includeFullDetails` (type: `boolean`): Open each posting to capture the complete description, posted date, and work type. Costs one more request per job. ## `resultsLimit` (type: `integer`): Hard cap on how many postings to gather across all terms and places combined. ## `timeoutSeconds` (type: `integer`): How long to wait on a single request before giving up. Bump it higher on slower proxy tiers. ## Actor input object example ```json { "jobSearchTerms": [ "customer success manager", "warehouse associate", "react developer" ], "searchLocations": [ "Chicago, IL", "Seattle, WA", "Remote" ], "includeFullDetails": false, "resultsLimit": 20, "timeoutSeconds": 90 } ``` # 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 = { "jobSearchTerms": [ "registered nurse" ], "searchLocations": [ "Denver, CO" ] }; // Run the Actor and wait for it to finish const run = await client.actor("data_api/ziprecruiter-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 = { "jobSearchTerms": ["registered nurse"], "searchLocations": ["Denver, CO"], } # Run the Actor and wait for it to finish run = client.actor("data_api/ziprecruiter-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 '{ "jobSearchTerms": [ "registered nurse" ], "searchLocations": [ "Denver, CO" ] }' | apify call data_api/ziprecruiter-jobs-scraper-cheap --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_api/ziprecruiter-jobs-scraper-cheap", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ZipRecruiter Jobs Scraper (Cheap)", "description": "ZipRecruiter Jobs Scraper collects job listings by keyword and location. You get titles, salaries, company names, and descriptions in a clean dataset, ready to use.", "version": "0.0", "x-build-id": "lL7ngdzbE8dmASM0S" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_api~ziprecruiter-jobs-scraper-cheap/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_api-ziprecruiter-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_api~ziprecruiter-jobs-scraper-cheap/runs": { "post": { "operationId": "runs-sync-data_api-ziprecruiter-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_api~ziprecruiter-jobs-scraper-cheap/run-sync": { "post": { "operationId": "run-sync-data_api-ziprecruiter-jobs-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "jobSearchTerms" ], "properties": { "jobSearchTerms": { "title": "Job search terms", "type": "array", "description": "Roles, skills, or keywords to look up — one per line. Each line triggers its own search.", "items": { "type": "string" } }, "searchLocations": { "title": "Search locations", "type": "array", "description": "Cities and states to cover, such as 'Denver, CO'. Leave it blank for a nationwide or remote sweep. Every location is paired with every search term.", "items": { "type": "string" } }, "includeFullDetails": { "title": "Pull full posting details", "type": "boolean", "description": "Open each posting to capture the complete description, posted date, and work type. Costs one more request per job.", "default": false }, "resultsLimit": { "title": "Results limit", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Hard cap on how many postings to gather across all terms and places combined.", "default": 20 }, "timeoutSeconds": { "title": "Timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "How long to wait on a single request before giving up. Bump it higher on slower proxy tiers.", "default": 90 } } }, "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 } } } } } } } } } } ```