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Economists & University Researchers

Job Market Data for Academic Research

900M+ unique postings from 2022 to present, all 82 enriched fields retained for reproducibility

Longitudinal dataset for labor economics: wage dynamics, skill demand, remote work adoption

The Canaria dataset enables empirical analysis across multiple labor economics domains: wage dynamics, skill requirements, remote work trends, and firm-level hiring behavior. All enrichment methodology is fully documented and published for peer review, and every raw, parsed, and enriched field is retained so results are reproducible.

Common Challenges

✕Commercial labor market datasets are black boxes with no published methodology, making peer review impossible
✕Raw scraped data requires months of cleaning before analysis: deduplication, location parsing, and salary normalization
✕Historical data with sufficient coverage for longitudinal studies is either unavailable or prohibitively expensive
✕SOC codes in most commercial sources use title-only matching, which misclassifies roles with ambiguous titles

How Canaria Helps

  • ✓Full methodological documentation published as a PDF covering deduplication, SOC classification, and salary prediction
  • ✓All raw, parsed, and enriched fields retained in delivery for auditing and reproducibility checks
  • ✓Historical archive from 2022 to present with daily updates, suitable for longitudinal and panel studies
  • ✓Academic pricing available: 50% off standard tiers with .edu verification

Example Use Cases

  1. 1Analyze wage dynamics by SOC code and MSA using stated and predicted salary fields from 2022 to present
  2. 2Study remote work adoption trends using work mode classification across 900M+ postings over three years
  3. 3Train NLP models for job description understanding using 900M+ records with SOC and skills ground truth labels

Relevant Data Fields

correctDatesocsalaryAvgAnnualnlpSkillsremoteseniorityfinalStatecompanyIndustry

These are a subset of the 82 fields available in every Canaria record.

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