Dataset

global-job-postings-multi-ats

Jobs & Workforce Download 1 source

Global Job Postings – Multi-ATS is a single dated snapshot of 112,816 job listings aggregated from 23 applicant tracking systems and parsed into a 47-column schema by NextGig-Rocks. It is distributed as Parquet via the Hugging Face datasets library and targets labor-market research, not production job boards.

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What this dataset contains

The release covers roughly 100,000 to 1 million rows drawn from Workday, Greenhouse, Lever, Ashby, iCIMS, SmartRecruiters, Oracle Cloud, Workable, and Paylocity among other ATS vendors. Each row is enriched with extracted skills, salary ranges, qualifications, experience level, work model, and geocoded latitude and longitude, making it a self-contained labor-market cross-section rather than a live feed. The publisher labels it a point-in-time research snapshot, and notes that original posting text has been summarized or replaced.

Structure and fields

The published column schema begins with identification and classification fields such as title, normalized_title, company_name, ats_name, industry, function, occupational_category, employment_type, work_model, schedule, shift, experience_level, and job_level_normalized. Compensation and qualification fields include years_experience_numeric, education_level, skills_required, minimum_qualifications, preferred_qualifications, responsibilities, certifications, languages_required, salary_min, salary_max, salary_currency, salary_rate_unit, salary_type, pay_frequency, bonus, equity, and on_target_earnings. List-type columns such as skills_required and minimum_qualifications are stored as JSON strings and need to be parsed with json.loads before analysis.

How analysts use it

Analysts can aggregate salary_min and salary_max across ats_name or industry to benchmark compensation, or pivot skills_required and occupational_category to track hiring demand by technology or role. The combination of geocoded postings, employment_type, and work_model supports regional labor-market studies and remote-work trend analysis. Because the snapshot is dated and intentionally non-live, it is best suited for retrospective research on hiring patterns, skill demand, and pay dispersion rather than real-time signals.

Documentation & references 1
  1. NextGig-Rocks/global-job-postings-multi-ats: listing on Hugging Face

Further reading

All guides
  • What is alternative data?Alternative data in investment research: what the term covers, how it differs from data format, and why provenance, timing, access and validation matter.
  • Job postings as an investment signalWhy hiring data predicts fundamentals: growth intent, expansion geography, technology adoption and cost control, how postings are collected, structured and turned into tradeable indicators.
  • Web scraping and compliance in alternative dataHow scraped datasets are actually collected, where terms of service and computer-muse laws draw lines, what hiQ v. LinkedIn settled and did not, and the diligence checklist for legally fragile data.
  • Free alternative data sourcesThe practical list of free alternative-data sources for investors: public filings, official statistics, satellite and earth observation, on-chain data, web archives and open registries, what each covers, what it costs in engineering effort, and where free data falls short.
  • Alternative data for investingHow funds turn alternative data into an investment edge: signal families, evaluation, backtesting, compliance and the build-vs-buy decision, mapped to the datasets and providers indexed on this encyclopedia.
  • Job market data: datasets and providersThe datasets and providers behind labor-market signals: job postings, payroll, employee profiles and job-change data, what each source measures, its caveats and how to choose one.

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