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PyronetsPyronets
Labor Market Data

Job Listings Data at Any Scale

We collect, structure, and deliver job postings from any job board, company career page, or industry-specific site, deduplicated, normalized, and ready for labor market analysis.

Postings, deduplicated

The same role on five boards should be one row, not five.

Cross-board
Duplicate postings resolved to a single record
Salary parsed
Ranges split into typed low and high values
First seen
Posting date recorded, not the date we collected it
See the receipts
The problem

Comprehensive labor market data is difficult to access reliably

Job postings are scattered across hundreds of boards, company websites, and niche platforms. Aggregating them into a consistent, deduplicated dataset requires ongoing engineering effort most organizations cannot sustain internally.

  • Job boards differ significantly in structure, requiring custom scraping logic for each source
  • Deduplication is complex: the same posting appears on multiple platforms with minor variations
  • Salary data is inconsistently formatted or entirely absent and requires standardization and inference
  • Postings expire, update, or get removed, requiring continuous recollection to maintain dataset freshness
  • Company career pages require ongoing monitoring and are often the first place new roles appear
Our approach

Structured, deduplicated job data from every source that matters

Pyronets collects job postings from any combination of job boards, aggregators, and company career pages, structured into consistent fields, deduplicated across sources, and delivered on your schedule.

What you get instead

Structured records in your schema, not raw HTML
Extraction repaired by us when sources change
Delivery on a fixed schedule, with a QA report attached
Scope this dataset

What you get

Multi-Source Board Coverage

Collect from Indeed, LinkedIn, Glassdoor, ZipRecruiter, Reed, Totaljobs, and any niche or regional job board. Add company career pages for first-party posting data.

Structured Field Extraction

Every posting is parsed into consistent structured fields: job title, company, location, employment type, salary range, skills required, description, and posting date.

Cross-Source Deduplication

The same posting often appears on multiple boards. We detect and deduplicate using job title, company, location, and description similarity so you count each opening once.

Salary Normalization

Salary data comes in many formats, hourly, annual, ranges, and narrative text. We extract and normalize to consistent annual salary ranges with currency codes.

Remote Status & Location Parsing

Remote, hybrid, and on-site status is extracted and standardized. Location is parsed into city, state, and country components for geographic analysis and filtering.

Freshness & Change Tracking

Daily or more frequent collection keeps the dataset current. New postings are flagged, expired postings are marked closed, and reposted roles are linked to their predecessors.

Schema

Fields we collect.

A starting point, not a fixed list, the final schema is whatever you sign off on during scoping.

Job Title
Exact title as posted and normalized canonical form
Company Name
Hiring company name, normalized across sources
Location
City, state/region, country, and full address where available
Remote Status
Remote, hybrid, on-site, or flexible classification
Employment Type
Full-time, part-time, contract, internship, freelance
Salary Range
Min, max, and midpoint in annual equivalent with currency
Required Skills
Extracted skill list from job description text
Seniority Level
Inferred or stated level: entry, mid, senior, director
Job Description
Full cleaned body text of the posting
Posting Date
Date the position was first published
Expiry / Closed Date
Date the posting was removed or marked filled
Source Board
Job board or career page the posting was collected from
Process

How your pipeline gets built

From first conversation to recurring delivery, with a sample you sign off on before anything runs on a schedule.

01

Define Sources & Filters

Specify which job boards, company career pages, regions, job categories, and industries to cover. Define any keyword or category filters to scope the collection.

02

Collection Pipeline Build

Custom scrapers are built for each source with field extraction, normalization, deduplication logic, and salary parsing configured to your requirements.

03

Sample Review

A representative sample covering all sources is delivered for your review. You confirm field quality, coverage, and deduplication accuracy before full collection.

04

Ongoing Delivery

Full collection runs on your schedule with incremental updates or full snapshots. Freshness, coverage, and quality metrics are reported with every delivery.

Applications

Common use cases.

01

Labor Market Analytics

Track hiring trends, in-demand skills, salary shifts, and geographic demand patterns over time for workforce planning, research, or consultancy deliverables.

02

Recruiting Intelligence

Monitor competitor hiring activity in real time (which roles they are filling, at what seniority, and in which locations) to inform talent strategy and competitive intelligence.

03

Compensation Benchmarking

Build salary benchmark datasets from posted ranges across geographies, seniority levels, and industries to support HR compensation planning and job grading.

04

Skills Gap Analysis

Analyze which technical and soft skills appear most frequently in postings for target roles to inform training programs, curriculum design, or hiring criteria.

05

Job Board & Aggregator Products

Supply a continuously updated job dataset to power search, recommendation, or matching features within HR tech products and job aggregator platforms.

06

Economic Research

Provide structured labor market signals to economists, policy researchers, and think tanks tracking employment conditions, sector growth, and wage dynamics.

Delivery formats

Pick whatever drops straight into your stack.

CSVExcel (XLSX)JSONJSON Lines (JSONL)REST APISFTPBigQueryDatabase Insert

Industries served

Where this dataset tends to be used.

HR Tech & RecruitingEconomic ResearchFinancial ServicesStaffing & Talent AcquisitionEducation & TrainingGovernment & PolicyManagement ConsultingTechnology & SaaS
Quality

Validated before it reaches you.

Every batch runs the full validation suite before delivery. If a batch fails, it does not ship. We investigate and repair the extraction first, and you get told what happened.

Type conformance
Every field matches its declared type
Range and sanity
Values fall inside agreed bounds
Null-rate thresholds
Coverage flagged when it drops
Duplicate resolution
Resolved against your chosen key
Schema drift
Source structure changes caught early
Volume variance
Unexpected record counts halt delivery
Questions

Frequently asked questions

Yes. Company career pages are often the first place roles appear. We build individual scrapers for any career page you specify, including ATS-powered pages using Workday, Greenhouse, Lever, and similar systems.

We use a combination of exact and fuzzy matching on job title, company, location, and description to detect cross-source duplicates. Each unique role gets a stable deduplication ID linking all its appearances.

Salary data availability depends on posting and platform. Where salary is stated, we extract and normalize it. Where it is absent, the salary field is null. We never fabricate or impute salary estimates.

We support daily or more frequent updates. New postings are appended, expired postings are marked as closed, and re-posted roles are flagged. Most clients use daily incremental updates.

Yes. Collection can be scoped by job category, keyword, industry, location, seniority level, or any combination. Filters are applied at collection time to keep datasets relevant and manageable.

Tell us the sources. We'll send back a sample.

Describe the sites and the fields you need. You'll get a proposed schema, a real sample extracted from those sources, and a fixed price, before any commitment.

No retainer required to find out whether your sources are feasible.

Sectors this data serves

Sectors this dataset commonly serves. Schema and cadence are set per project.

HR Tech PlatformsWorkforce AnalyticsJob AggregatorsRecruitment AgenciesLabor Market ResearchSalary BenchmarkingTalent IntelligenceGovernment Stats

Sample output

An illustrative preview of delivered records. The real schema is whatever you sign off on.

sample_output.csv
job_titlecompanylocationsalary_rangeposted_atsource
Senior Data EngineerGoogleRemote, USA$180,000 – $220,0002025-05-18LinkedIn
ML Research ScientistAmazonSeattle, WA$200,000+2025-05-17Indeed
Analytics EngineerStripeSan Francisco, CA$160,000 – $190,0002025-05-15Greenhouse
3 of 3,241,890 records shown · CSV · Delivered daily at 06:00 UTC

How We Deduplicate 800+ Sources

The same job posting appears across many boards. We normalize and deduplicate to deliver each unique role exactly once.

12x
Average duplicates per role
Same job on LinkedIn, Indeed, Glassdoor, company site, etc.
Deduplication Engine
Company + Title + Location + Date matching with fuzzy logic normalization
Clean unique record
Normalized fields, source attribution, and enriched metadata.