Salary Intelligence
Predicted and reported salary data across 1B+ job postings. Our salary prediction model is trained on 50M+ salary observations with three-source fusion across posted ranges, employee-reported pay, and BLS OES benchmarks, producing 44,000+ benchmark cells with 95% confidence intervals. Every record gets a predicted salary, even when the posting doesn't include one.
How Salary Prediction Works
50M+ salary observations from posted ranges, employee-reported pay, and BLS OES benchmarks, covering all industries and geographies.
Title, description, location, company, industry, seniority, skills, and SOC code feed the model.
Min, max, and average annual salary prediction on every record, reported across 44,000+ SOC-by-state benchmark cells with 95% confidence intervals.
Sample Records
| Job Title | Company | City | State | Seniority | Work Mode | Min Salary | Max Salary | SOC Code | SOC Title | +8 more |
|---|---|---|---|---|---|---|---|---|---|---|
| Machine Learning Engineer | Fortune 500 tech company | San Jose | CA | Senior | Hybrid | 190,000 | 280,000 | 15-2051 | Data Scientists | … |
| Financial Analyst | Global investment bank | New York | NY | Mid | On-site | 95,000 | 135,000 | 13-2051 | Financial Analysts | … |
| DevOps Engineer | Cloud monitoring platform | Boston | MA | Mid | Remote | 140,000 | 185,000 | 15-1244 | Network Architects | ... |
| Pharmacist | National pharmacy chain | Chicago | IL | Mid | On-site | 120,000 | 145,000 | 29-1051 | Pharmacists | ... |
| UX Designer | Design software company | 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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Salary data from a recent 30-day sample of our 1B+ posting dataset
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Access predicted salaries on every record with min, max, and average annual values. Filter by role, location, seniority, and industry.
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