Salary Data
Combined compensation intelligence from three sources: AI-predicted salaries trained on 50M+ observations with three-source fusion (posted, reported, BLS OES) and 95% confidence intervals across 44,000+ SOC-by-state benchmark cells, parsed posted salaries from job listings, and ~11M employee-reported Glassdoor salary records. Predicted salary coverage is 85-95% for 2023+ postings; stated salary coverage is 40-60% for 2023+ (rising due to US transparency laws). All salaries are normalized to annual USD with the invariant min <= avg <= max always enforced. Predictions require valid US State + ZipCode + SOC code and return -1 when prerequisites are missing.
AI-predicted salaries are generated by our salary regression model. Parsed posted salaries and Glassdoor reports are preserved alongside predictions for full transparency.
Key Highlights
- Three salary sources combined: AI-predicted, parsed posted, and employee-reported (Glassdoor)
- Three-source fusion (posted, reported, BLS OES) with 95% confidence intervals across 44,000+ benchmark cells, trained on 50M+ Glassdoor/Indeed observations
- ~11M Glassdoor employee-reported salary records for ground-truth benchmarking
- Invariant enforced: salary_min <= salary_avg <= salary_max (always holds)
- All salaries normalized to annual USD regardless of original format
- Transparency law impact tracked: stated salary coverage rising from <20% pre-2022 to 40-60% in 2023+
Use Cases
- Compensation benchmarking and pay equity analysis
- HR tech salary features and recommendations
- Investment signals from labor cost trends
- Workforce planning budgets and headcount modeling
Sample FieldsView full schema
parsedAnnualSalaryMinparsedAnnualSalaryAvgparsedAnnualSalaryMaxnlpSalaryscrapedSalarysocfinalStatezipCodeDelivery Formats
See This Data Live
Interactive charts from our 1B+ deduplicated job postings, updated daily.
Sample Records
A preview of real records from this dataset. Unlock all fields by requesting a free sample.
| Job Title | Company | City | State | Seniority | Work Mode | Min Salary | Max Salary | SOC Code | SOC Title | +8 more |
|---|---|---|---|---|---|---|---|---|---|---|
| Machine Learning Engineer | Meta | Menlo Park | CA | Senior | Hybrid | 190,000 | 280,000 | 15-2051 | Data Scientists | … |
| Financial Analyst | Goldman Sachs | New York | NY | Mid | On-site | 95,000 | 135,000 | 13-2051 | Financial Analysts | … |
| DevOps Engineer | Datadog | Boston | MA | Mid | Remote | 140,000 | 185,000 | 15-1244 | Network Architects | ... |
| Pharmacist | CVS Health | Chicago | IL | Mid | On-site | 120,000 | 145,000 | 29-1051 | Pharmacists | ... |
| UX Designer | Figma | San Francisco | CA | Senior | Remote | 155,000 | 210,000 | 27-1024 | Graphic Designers | ... |
Illustrative sample records showing the delivered schema. Real records are delivered via sample request.
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More Datasets
Canaria delivers five integrated datasets that join cleanly with each other.
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1B+ deduplicated job postings from Indeed, LinkedIn, ATS, and 15+ sources
Company Profiles
28.5M company profiles with firmographics, hiring signals, and industry classification
Skills & Occupation Taxonomy
40,000+ skills, 3,400+ certifications, SOC codes, and normalized titles
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Frequently Asked Questions
Common questions about the Salary Data dataset.
- What salary sources does the dataset combine?
- Three signals per record: AI-predicted salaries trained on 50M+ observations with three-source fusion (posted, reported, BLS OES), parsed posted salaries, and ~11M employee-reported Glassdoor records.
- What is the salary coverage?
- Predicted salary coverage is 85-95% for 2023+ postings; stated posted-salary coverage is 40-60% for 2023+, rising due to US pay-transparency laws.
- How are salaries normalized?
- All salaries are normalized to annual USD, with the invariant minimum <= average <= maximum always enforced.
- What inputs does the prediction require?
- Predictions require a valid US state, ZIP code, and SOC code, and return -1 when those prerequisites are missing.
- How precise are the benchmarks?
- Predicted ranges are reported across 44,000+ SOC-by-state benchmark cells, each with a 95% confidence interval.