Job Title vs. Occupation: What’s the Difference and Why It Matters
In labor market data, the terms job title and occupation are related, but they mean very different things. Understanding this distinction is key to using Lightcast data effectively.
What is a Job Title?
A job title is the label an employer or individual uses to describe a specific role. Titles can be highly specific, creative, or inconsistent, and they often vary across companies, industries, and regions. For example:
Principal Software Engineer
Senior Data Analyst
Income Tax Analyst
ICU Registered Nurse
These titles come directly from job postings and online profiles, and they typically follow no standardized structure. To make this data usable, Lightcast classifies raw titles into a standardized system of more than 70,000 Lightcast Titles.
Job titles are valuable for understanding how roles are described in real-world language, but they are not well suited for grouping similar jobs or conducting high-level comparisons across the labor market.
What is an Occupation?
An occupation is a collection of jobs that involve similar work, regardless of how those jobs are titled. Occupations are defined using structured classification systems, often referred to as taxonomies. These systems provide consistency and make it easier to compare roles across companies, industries, and locations. Lightcast supports several occupation taxonomies, including:
Each taxonomy organizes jobs based on shared responsibilities, required skills, and typical qualifications, not the specific words in a job title. For example, “Principal Software Engineer,” “Full Stack Developer,” and “DevOps Engineer” might all map to the same occupation.
When Should You Use Job Titles vs. Occupations?
Use job titles when:
You need precise targeting for talent research or competitive hiring analysis
You want to analyze how how companies and individuals describe roles in their own words
You are looking for emerging or niche roles that may not yet appear in standardized taxonomies
Use occupations when:
You need consistency or alignment with official government standards
You want to group similar roles together for clean comparisons
You are comparing labor data across locations, industries, or time periods
How This Affects Different Types of Data
Job titles are especially helpful when analyzing job postings or online profiles. These sources reflect how companies and individuals describe roles in their own words, so title-level analysis provides the most direct insight into how the market is talking about work.
However, if you're working with official government data or using models that rely on national labor force statistics, job titles are not enough. These sources are using occupation taxonomies like SOC, NOC, or Lightcast's own LOT. To access this sort of data, you need to use the appropriate occupation taxonomy.
Summary
In short, job titles help you understand what’s happening on the ground. Occupations help you connect that activity to formal labor statistics, benchmarks, and models. Both are valuable, and knowing which one to use depends on what question you are trying to answer.