# Research employer careers pages and published job evidence

**Use case:** 

Inspect careers routes and supported published jobs with dates when available. Keep employer context, source links and ten buyer perspectives.

## Input

```json
{
  "websites": [
    "https://about.gitlab.com/"
  ],
  "dataset_website_field": "website",
  "buyer_profile": "recruiting",
  "buyer_profiles": [
    "general",
    "recruiting",
    "web_agency",
    "automation_agency",
    "seo_agency",
    "ecommerce_agency",
    "crm_consulting",
    "analytics_consulting",
    "customer_support",
    "hospitality_tech"
  ],
  "contact_requirement": "any",
  "min_opportunity_score": 0,
  "exclude_domains": [],
  "sector": "it_services",
  "cities": [
    "San Francisco"
  ],
  "country_code": "US",
  "radius_km": 3,
  "language": "en",
  "max_results": 1,
  "max_requests": 25,
  "max_pages_per_company": 5,
  "timeout_seconds": 75,
  "paid_provider": "none",
  "max_paid_requests": 0,
  "ai_provider": "none",
  "include_web_experience": false,
  "max_crux_calls": 5,
  "max_ai_calls": 0,
  "max_output_tokens": 500,
  "include_jobs": true,
  "job_keywords": [],
  "job_max_age_days": 0,
  "max_jobs_per_company": 10,
  "max_job_requests_per_company": 2,
  "require_jobs": false,
  "employer_filter": "all",
  "check_email_domains": false,
  "max_email_domain_checks": 10,
  "monitor_id": "",
  "only_changes": false,
  "location_provider": "offline",
  "registry_provider": "none",
  "max_registry_requests": 0,
  "free_source_mode": "resilient",
  "signal_match": "all",
  "include_crm_review": true,
  "include_documents": false,
  "max_documents_per_company": 1,
  "max_document_pages": 3,
  "include_browser": false,
  "browser_timeout_seconds": 15
}
```

## Output

```json
{
  "name": {
    "label": "Name",
    "format": "string"
  },
  "business_id": {
    "label": "Business id",
    "format": "string"
  },
  "city": {
    "label": "City",
    "format": "string"
  },
  "research_priority": {
    "label": "Research priority",
    "format": "integer"
  },
  "jobs": {
    "label": "Jobs",
    "format": "array"
  },
  "job_scan_status": {
    "label": "Job scan status",
    "format": "string"
  },
  "change_types": {
    "label": "Change types",
    "format": "array"
  },
  "contact_freshness": {
    "label": "Contact freshness",
    "format": "string"
  },
  "first_seen": {
    "label": "First seen",
    "format": "string"
  },
  "last_seen": {
    "label": "Last seen",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Local Business Leads & Email Finder for Agencies Actor is ready to run with the inputs already set for "Research employer careers pages and published job evidence". [Sign up or log in](https://console.apify.com/create-task-from-example/fEQfvrHpVw8uC8qEC) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Research employer careers pages and published job evidence" task

The Local Business Leads & Email Finder for Agencies Actor will start running based on the input automatically. You can also change all the input fields, like import company websites, dataset company website field, and more, to match your specific use case.

### 3. Receive the "Research employer careers pages and published job evidence" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as name, business id, city, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Research employer careers pages and published job evidence" task via API](https://apify.com/ryanbot_research/ryanbot-company-research.md).

## FAQ

### Do ten profiles guarantee ten useful findings?

No. The profiles organize shared observed evidence. Missing contacts, jobs or commerce findings stay explicit. Review source links and gaps before using the output.

### What does this example cost?

Normal qualified-report, start and Apify usage fees apply. Saved cap: USD 0.05/run, 256 MB, 120 seconds. No paid search, AI or schedule. Start and usage costs may apply without a qualified report.

### Can I use my own website?

Replace the example URL and choose its country and sector. Start with one site. The example is not an endorsement; coverage depends on readable public sources and run limits.

## About this Actor

This example demonstrates how to use [Local Business Leads & Email Finder for Agencies](https://apify.com/ryanbot_research/ryanbot-company-research.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/ryanbot_research/ryanbot-company-research.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/ryanbot_research/ryanbot-company-research.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).