We started PredictLeads with the mission to find actionable business data in public documents. One of our innovations includes the Job Openings Dataset, which provides valuable insights for businesses.

HISTORY

Job postings were always among the most valuable business signals we tracked. Early on, our clients asked not just for news and funding events, but for insights into who companies were hiring, for what roles, and in which locations.

The challenge was that job data scattered across thousands of careers pages was unstructured, messy, and difficult to normalize. For example, one company may post “Software Developer” while another writes “Backend Engineer” — but both describe similar roles. Without standardization, insights were limited.

After months of developing crawling systems, mapping roles to O*NET occupation codes, and building quality checks, we’re proud to launch the Job Openings Dataset.

FUTURE

At its core, the Job Openings Dataset performs three key steps:

1. Scan millions of company websites and career pages daily.
   Public source examples: job boards, ATS systems, company career portals.
2. Extract and normalize job posting data.
   Entity examples: job title, description, salary, location, categories, seniority.
3. Map jobs to standardized frameworks.
   Using O*NET codes and predictive tagging, postings are classified into consistent roles and families.

And just like with our other datasets, we apply a human supervision layer — ensuring the highest possible quality in classification and normalization.

EXAMPLES

To better picture the type of data, here are two JSON examples:

Job Opening Example (Engineering Role)

{
  "id": "4d5ac23c-5824-427d-96c6-4e8d50a4241a",
  "type": "job_opening",
  "title": "AI Engineer",
  "url": "https://www.ycombinator.com/companies/terra-api/jobs/0f5CP0r-ai-engineer",
  "first_seen_at": "2025-09-28T19:11:05Z",
  "last_seen_at": "2025-09-29T07:19:46Z",
  "categories": ["engineering"],
  "onet_data": {
    "code": "15-1252.00",
    "family": "Computer and Mathematical",
    "occupation_name": "Software Developers"
  },
  "salary_data": {
    "salary_low": 50000.0,
    "salary_high": 120000.0,
    "salary_currency": "USD",
    "salary_time_unit": "year"
  },
  "seniority": "non_manager",
  "language": "en",
  "location": "London, United Kingdom",
  "tags": ["Python", "Ruby", "JavaScript"]
}

Job Opening Example (Marketing Role)

{
  "id": "6a9f52b0-9b71-47a8-bc04-7d5e57dd2af1",
  "type": "job_opening",
  "title": "Marketing Manager",
  "url": "https://www.example.com/jobs/marketing-manager",
  "first_seen_at": "2025-09-20T10:15:00Z",
  "last_seen_at": "2025-09-28T12:45:00Z",
  "categories": ["marketing"],
  "onet_data": {
    "code": "11-2021.00",
    "family": "Management",
    "occupation_name": "Marketing Managers"
  },
  "salary_data": {
    "salary_low": 70000.0,
    "salary_high": 95000.0,
    "salary_currency": "USD",
    "salary_time_unit": "year"
  },
  "seniority": "manager",
  "language": "en",
  "location": "New York, United States",
  "tags": ["Content Marketing", "SEO", "ABM"]
}

These are just 2 of 30+ categories supported (engineering, marketing, sales, finance, HR, and more). Full schema is available here: https://predictleads.com/docs/#job_openings

APPLICATIONS

The types of applications are (almost) endless, but here are a few we see most often:

• Sales Enablement Solutions: identify prospects investing in teams relevant to your product.
• Predictive Lead Scoring: hiring signals are some of the strongest intent indicators for buying readiness.
• Account Based Marketing or Sales: personalize outreach with context such as “just hired a new Marketing Manager” or “expanding their engineering team in London.”
• Recruiting & Talent Intelligence: map hiring velocity across roles, salaries, and geographies.
• Market Analysis: spot industry-wide demand trends and role scarcity early.

CONTACT

Get access to the Job Openings Dataset or request your API key:

📧 sales@predictleads.com