Salary Benchmarking

Lightcast data helps answer evolving salary and compensation questions across roles, skills, and markets. These use cases show how to retrieve advertised wages, market salary benchmarks, and national salary metrics using standardized occupations and skills.

Use Cases

Standard Occupational Classification (SOC) Level Compensation Insights

Normalize a raw job title to the government Standard Occupational Classification (SOC), and then use that SOC to retrieve related compensation data.

APIs Used

Python Example

Get Advertised Wages for a Given Lightcast Occupational Taxonomy (LOT)

Normalize a raw job title to the Lightcast Occupational Taxonomy (LOT), and then use job postings data to retrieve wages for the related occupation.

APIs Used

Python Example

Market Salary for a Role

Normalize raw job titles to the Lightcast Occupational Taxonomy (LOT), and then use the Market Salary API to retrieve salary benchmarks for the related role.

APIs Used

Python Example

National Salary Metrics for Lightcast Occupational Taxonomy (LOT)

Normalize raw job titles to the Lightcast Occupational Taxonomy (LOT), and then retrieve national salary percentiles for the related occupation.

APIs Used

Python Example

National Salary Metrics for Skills

Normalize raw skills to standardized skills, and then retrieve national salary percentiles associated with those skills.

APIs Used

Python Example