# Otta Jobs Scraper (Welcome to the Jungle) (`scrapeworks/otta-jobs-scraper`) Actor Scrape Otta / Welcome to the Jungle job listings in bulk: title, salary range, tech stack, remote policy, experience level, description bullets, plus company funding, headcount and Glassdoor rating. By company, by job URL, or the whole board - 30,000+ live jobs. No login needed. - **URL**: https://apify.com/scrapeworks/otta-jobs-scraper.md - **Developed by:** [Nicolas van Arkens](https://apify.com/scrapeworks) (community) - **Categories:** Jobs, Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 33.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Otta Jobs Scraper — Welcome to the Jungle Job Listings with Salaries Scrape job listings from **Otta** (now **Welcome to the Jungle**, app.welcometothejungle.com — old otta.com links work too) in bulk. Otta is the curated tech job board used by startups and scale-ups like Stripe, Monzo, Anthropic, Anduril and 3,000+ other hiring companies — and unlike most job boards, **most listings carry a real salary range** (84% of rows in testing). Every row is one job with salary, tech stack, remote policy, experience level, full description bullets and a direct apply link — **plus company intelligence on the same row**: headcount, total funding (USD), last round, top investors, sectors, Glassdoor and Trustpilot ratings, employee growth. No login, no API key. ### What you get per job | Field | Description | |---|---| | `title`, `subtitle`, `function`, `subFunction` | Role name and Otta's function taxonomy (e.g. Software Engineering → Backend Engineer) | | `salaryMin`, `salaryMax`, `salaryCurrency` | Real salary range (GBP/USD/EUR…), filled on most rows; `oteSalaryMin/Max` for OTE roles | | `minYearsExperience`, `maxYearsExperience`, `internship` | Experience band | | `locations`, `locationCodes`, `remoteOnly`, `minDaysInOffice`, `maxDaysInOffice` | Offices + remote/hybrid policy, days-in-office band | | `locationInformation`, `locationRestrictions` | Visa sponsorship / relocation notes when offered | | `technologies` | Tech stack tags (React, Go, AWS, Kubernetes…) | | `involves` | Full "what you'll do" description bullets | | `requirements` | Requirement bullets, each flagged `desirable` true/false | | `applyUrl` | Direct application URL (usually the company's Greenhouse/Lever/Ashby posting) | | `url`, `jobExternalId` | Canonical Welcome to the Jungle job link + stable ID | | `firstLiveAt`, `lastSeen`, `daysSincePosted`, `activelyHiring` | Freshness signals | | `companyName`, `companyWebsite`, `companyDescription`, `companyHq` | Employer basics | | `companyEmployees`, `companySize`, `companyEmployeeGrowthPct`, `companyPercentFemale` | Headcount and growth | | `companyTotalFundingUsd`, `companyLastFundingRound`, `companyLastFundingYear`, `companyInvestors` | Funding profile (Dealroom-backed) | | `companyGlassdoorRating`, `companyTrustpilotRating`, `companySectors`, `companyLiveJobs` | Reputation + sector tags | ### Three ways to run it (combine freely) 1. **By company** — list company names, slugs or profile URLs; you get every live job of each company: ```json { "companyNames": ["Monzo", "Stripe", "Salesforce"], "maxResults": 200 } ```` 2. **Whole-board sweep** — enumerate all 18,000+ companies (~3,000 actively hiring, 30,000+ live jobs) and scrape everything, biggest employers first. This turns on automatically when you give no companies and no job URLs: ```json { "discoverAllCompanies": true, "keywords": ["backend", "python", "machine learning"], "maxResults": 5000, "maxJobsPerCompany": 50 } ``` 3. **Specific jobs** — paste job URLs (or the short IDs from them): ```json { "jobUrls": ["https://app.welcometothejungle.com/jobs/WqaVPKhj", "FVO1DH1o"] } ``` `keywords` filters case-insensitively across title, function, tech stack and company name. Results are de-duplicated across all modes; `maxResults` caps total billed rows. ### Example output row (real data) ```json { "title": "Senior Staff Backend Engineer", "url": "https://app.welcometothejungle.com/jobs/WqaVPKhj", "function": "Software Engineering", "subFunction": "Backend Engineer", "salaryMin": 135000, "salaryMax": 184000, "salaryCurrency": "GBP", "minYearsExperience": 5, "maxYearsExperience": 10, "locations": ["London", "Remote Uk", "Cardiff"], "remoteOnly": false, "minDaysInOffice": 0, "maxDaysInOffice": 5, "locationInformation": "We'll help you relocate to the UK, We can sponsor your visa", "technologies": ["React", "AWS", "Docker", "Kubernetes", "GCP", "Kafka", "Go", "Cassandra"], "involves": ["A Senior Staff Engineer at Monzo is a hands on engineering leadership (IC) position...", "..."], "requirements": [{"requirement": "You have a track record of leading complex, high-impact systems...", "desirable": false}], "applyUrl": "https://job-boards.greenhouse.io/monzo/jobs/6036797?utm_source=Otta", "companyName": "Monzo", "companyEmployees": 5300, "companyTotalFundingUsd": 1923750000, "companyLastFundingRound": "LATE VC", "companyInvestors": ["Y Combinator", "Accel", "GV", "Coatue Management", "..."], "companyGlassdoorRating": 3.9, "companySectors": ["Fintech", "B2C", "Banking", "..."] } ``` ### Use cases - **Salary benchmarking** — Otta is one of the few boards where most listings publish a real salary range; pull thousands of salary-tagged roles by function, tech or location. - **Recruiting & talent intelligence** — track who is hiring for what, at which seniority, with which stack; `applyUrl` links straight into the employer's ATS. - **Sales lead generation** — every row carries funding, headcount growth and investors: filter to "well-funded companies hiring backend engineers" and you have an account list. - **Job aggregation** — feed a niche job board or newsletter with fresh, structured, salary-transparent tech jobs. - **Market research** — tech-stack adoption and remote-policy trends across 3,000 hiring startups. ### FAQ **Do I need an Otta / Welcome to the Jungle account?** No. The actor reads the same public API the website itself uses — no login, no cookies. **How many jobs can one run return?** A full board sweep holds 30,000+ live jobs across ~3,000 hiring companies. `maxResults` (default 2,000) bounds the run. **Why do some rows have no salary?** A minority of employers hide compensation (`salaryHidden: true`) or never provided it. In testing, ~84% of rows carried a numeric range. **Are old otta.com job links supported?** Yes — otta.com and app.welcometothejungle.com job URLs (and bare short IDs like `WqaVPKhj`) all resolve. **What about the French/global welcometothejungle.com site?** This actor covers the Otta board (app.welcometothejungle.com — the UK/US-centric curated tech board). The separate legacy French site is not this catalog. **How fresh is the data?** Live jobs only — each row includes `firstLiveAt`, `lastSeen` and `daysSincePosted` so you can filter to the newest postings. **Is it billed per run or per row?** Pay per event: each job row returned is charged once. Failed lookups, blocked requests and duplicates are never charged. # Actor input Schema ## `companyNames` (type: `array`): Companies to scrape ALL live jobs for. Accepts the company name ("Monzo"), the URL-safe slug ("10x-Banking") or the full profile URL ("https://app.welcometothejungle.com/companies/Monzo"). Every live job of every listed company becomes one output row. Leave empty (together with Job URLs) to sweep the ENTIRE job board instead. ## `jobUrls` (type: `array`): Individual job listings to fetch. Accepts full job URLs ("https://app.welcometothejungle.com/jobs/WqaVPKhj", old otta.com links work too) or just the short job ID ("WqaVPKhj"). Combine freely with Companies - everything is merged and de-duplicated. ## `discoverAllCompanies` (type: `boolean`): Enumerate EVERY company on Otta / Welcome to the Jungle (18,000+, ~3,000 actively hiring) and scrape all their live jobs - 30,000+ jobs on a full sweep. Turns on automatically when both lists above are empty. Use Max results to bound the run. ## `keywords` (type: `array`): Only keep jobs matching at least one keyword (case-insensitive) in the job title, function, sub-function, tech stack or company name - e.g. "backend", "product manager", "python", "machine learning". Leave empty to keep every job. ## `maxResults` (type: `integer`): Overall cap on jobs returned (after de-duplication and keyword filtering). A full board sweep holds 30,000+ live jobs; the default of 2000 keeps a run bounded. Every job returned is billed once. ## `maxJobsPerCompany` (type: `integer`): Cap on jobs taken from any single company (biggest employers list 50+). Keeps a board sweep spread across many companies. Default 500 = effectively no cap. ## `proxyConfiguration` (type: `object`): Fallback proxy for reaching the Otta API. Requests go DIRECTLY first and only route through this proxy if blocked or rate-limited. The default (Apify Residential) is a safe fallback; leave it in place. ## Actor input object example ```json { "companyNames": [ "Monzo", "Deliveroo", "Revolut", "https://app.welcometothejungle.com/companies/Wise" ], "jobUrls": [ "https://app.welcometothejungle.com/jobs/WqaVPKhj", "FVO1DH1o" ], "discoverAllCompanies": false, "keywords": [ "backend", "python", "machine learning" ], "maxResults": 2000, "maxJobsPerCompany": 500, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "companyNames": [ "Monzo", "Deliveroo", "Revolut" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeworks/otta-jobs-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 = { "companyNames": [ "Monzo", "Deliveroo", "Revolut", ], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("scrapeworks/otta-jobs-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 '{ "companyNames": [ "Monzo", "Deliveroo", "Revolut" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call scrapeworks/otta-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeworks/otta-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Otta Jobs Scraper (Welcome to the Jungle)", "description": "Scrape Otta / Welcome to the Jungle job listings in bulk: title, salary range, tech stack, remote policy, experience level, description bullets, plus company funding, headcount and Glassdoor rating. By company, by job URL, or the whole board - 30,000+ live jobs. No login needed.", "version": "0.1", "x-build-id": "NvZtxfzOrUK1X7t6D" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeworks~otta-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeworks-otta-jobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeworks~otta-jobs-scraper/runs": { "post": { "operationId": "runs-sync-scrapeworks-otta-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeworks~otta-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeworks-otta-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "companyNames": { "title": "Companies", "uniqueItems": true, "type": "array", "description": "Companies to scrape ALL live jobs for. Accepts the company name (\"Monzo\"), the URL-safe slug (\"10x-Banking\") or the full profile URL (\"https://app.welcometothejungle.com/companies/Monzo\"). Every live job of every listed company becomes one output row. Leave empty (together with Job URLs) to sweep the ENTIRE job board instead.", "items": { "type": "string" } }, "jobUrls": { "title": "Job URLs or IDs (optional)", "uniqueItems": true, "type": "array", "description": "Individual job listings to fetch. Accepts full job URLs (\"https://app.welcometothejungle.com/jobs/WqaVPKhj\", old otta.com links work too) or just the short job ID (\"WqaVPKhj\"). Combine freely with Companies - everything is merged and de-duplicated.", "items": { "type": "string" } }, "discoverAllCompanies": { "title": "Sweep the whole job board", "type": "boolean", "description": "Enumerate EVERY company on Otta / Welcome to the Jungle (18,000+, ~3,000 actively hiring) and scrape all their live jobs - 30,000+ jobs on a full sweep. Turns on automatically when both lists above are empty. Use Max results to bound the run.", "default": false }, "keywords": { "title": "Keyword filter (optional)", "uniqueItems": true, "type": "array", "description": "Only keep jobs matching at least one keyword (case-insensitive) in the job title, function, sub-function, tech stack or company name - e.g. \"backend\", \"product manager\", \"python\", \"machine learning\". Leave empty to keep every job.", "items": { "type": "string" } }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 200000, "type": "integer", "description": "Overall cap on jobs returned (after de-duplication and keyword filtering). A full board sweep holds 30,000+ live jobs; the default of 2000 keeps a run bounded. Every job returned is billed once.", "default": 2000 }, "maxJobsPerCompany": { "title": "Max jobs per company", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Cap on jobs taken from any single company (biggest employers list 50+). Keeps a board sweep spread across many companies. Default 500 = effectively no cap.", "default": 500 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Fallback proxy for reaching the Otta API. Requests go DIRECTLY first and only route through this proxy if blocked or rate-limited. The default (Apify Residential) is a safe fallback; leave it in place.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```