Occupation Overview

The occupation object describes a category of jobs such as electrical engineers, marketing managers, or machinists. Occupations are used in cases where candidates are exploring career transitions rather than seeking specific roles to apply for and in cases where employers are seeking to increase the number of viable candidates for open positions. AdeptID's occupation taxonomy is based on the O*NET Taxonomy, sponsored by the US Department of Labor.

📘

What is the difference between a job and an occupation?

In AdeptID’s data model, a job refers to a single job posting or work experience, while an occupation refers to a category of similar jobs. For example, a tax accountant at Bank of America, a public accountant at Merck, and an auditor at KPMG (three different jobs) are grouped together in the Accountants and Auditors occupation. In the O*NET taxonomy, Accountants and Auditors have an ID (13-2011.00) that is part of the Business and Financial Operations Occupation Group and has many other pieces of associated metadata.

AdeptID uses its Occupation Classification model to determine the occupation of inputted job postings or work experiences based on the job title, employer, and industry.

Metadata fields for occupation include demographics, typical salaries, and projected growth of the role. These are provided through Occupation Metadata.

Occupation Schema

The metadata fields available for each occupation are detailed below. For those fields that vary by location, data is typically available at the national, state and metropolitan statistical area level.

General Information

Information for naming, describing and categorizing occupations. We offer three systems for categorizing occupations: O*NET career clusters, O*NET job families, and AdeptID job categories. AdeptID categories are designed to align with typical corporate functions.

Demographics

Race/ethnicity and gender distributions by occupation and location. Demographic information can be used to compare the level of diversity between roles. Data may be unavailable in some cases.

Occupation Size and Growth

Information describing and categorizing the volume of supply and demand by occupation and location. Data may be missing in some cases.

Wages

Distribution of wages by occupation and location. Annualized and hourly wages are offered for the mean, median, 10th, 25th, 75th and 90th percentile. Data are sourced from the Bureau of Labor Statistics. Data may be unavailable in some cases.

Notes on Occupational Metadata

• Handling of Unavailable Data: In some cases, data sourced from the Bureau of Labor Statistics (BLS) may not be available. If the BLS has not published wage or projected growth data, we provide the data from the parent occupation in the SOC taxonomy. If the BLS has not provided employment data, we will return a NULL value.

• Demand Category Definition: The bins used to define demand_posting_category are scaled according to the total demand in the reporting location: The largest occupations accounting for 50% of the total demand in the reporting location are classified as Very High demand. The next largest occupations accounting for an additional 25% of total demand are tagged as High. Occupations accounting for an additional 10% of demand are classified as medium Medium demand, and the smallest occupations accounting for 5% of total demand are tagged as Low demand.

{
	"demographics": {
		"gender": {
			"female": 53.80351743611358,
			"male": 46.19648256388641
		},
		"race_and_ethnicity": {
			"american_indian_or_alaska_native": 0.41073252351138073,
			"asian": 4.810282264445744,
			"black_or_african_american": 12.139558924176125,
			"hispanic_or_latino": 17.20861875771386,
			"native_hawaiian_or_other_pacific_islander": 0.15517523450874074,
			"two_or_more_races": 1.9465603285654438,
			"white": 63.3290719670787
		}
	},
	"geography_name": "United States",
	"geography_type": "national",
	"occupation_supply_and_growth": {
		"demand_posting_category": "Very Large",
		"employment": 3640040,
		"posting_count": 1077407,
		"projected_national_growth": -2.1
	},
	"onet_metadata": {
		"career_cluster": "Marketing",
		"common_name": "Retail Sales Associates",
		"common_name_singular": "Retail Sales Associate",
		"description": "Sell merchandise, such as furniture, motor vehicles, appliances, or apparel to consumers.",
		"job_category_primary": "Retail",
		"job_category_secondary": "Sales",
		"job_family": "Sales and Related Occupations",
		"onet_code": "41-2031.00",
		"onet_name": "Retail Salespersons",
		"related_job_titles": [
			"Car Salesman",
			"Customer Assistant",
			"Retail Salesperson",
			"Sales Associate",
			"Sales Clerk",
			"Sales Consultant",
			"Sales Person",
			"Sales Representative",
			"Salesman"
		]
	},
	"wages": {
		"annual_10th_percentile_wage": 22590.0,
		"annual_25th_percentile_wage": 26950.0,
		"annual_75th_percentile_wage": 36090.0,
		"annual_90th_percentile_wage": 47200.0,
		"annual_mean_wage": 34730.0,
		"annual_median_wage": 30600.0,
		"hourly_10th_percentile_wage": 10.86,
		"hourly_25th_percentile_wage": 12.96,
		"hourly_75th_percentile_wage": 17.35,
		"hourly_90th_percentile_wage": 22.69,
		"hourly_mean_wage": 16.7,
		"hourly_median_wage": 14.71,
		"wage_quartile": 2
	}
}

Occupation Taxonomy

AdeptID’s occupation taxonomies offer a means of grouping individual jobs into broader categories. Our taxonomies are based on the O*NET occupational taxonomy, sponsored by the US Department of Labor. We support occupation taxonomies:

• O*NET 2019

• O*NET 2019 Simplified: an O*NET 2019 variant developed by AdeptID. O*NET 2019 Simplified removes some occupations to create a more user-friendly taxonomy.

📘

AdeptID Enhancements to O*NET

• Common Name: Familiar, non-technical names (e.g. Store Manager instead of First-Line Supervisors of Retail Sales Workers). Common names are available in singular and plural versions.
• O*NET Simplified Taxonomy: Smaller, more manageable occupation taxonomy removes rarely used occupations to ensure that occupational results will be clear and familiar to users.
• Job Categories: Groupings of occupations which align with typical corporate functions (e.g. Human Resources, Marketing, Engineering).

Use Cases for Occupation Taxonomies

AdeptID uses an occupational taxonomy and schema in support of the following use cases:

• Recommending Career Pathways for Candidates: In cases where candidates are exploring career transitions, AdeptID recommends occupational categories for them to consider rather than specific open job transitions. This use case is satisfied using Recommend Destination Occupations. (O*NET 2019 Simplified is the occupation taxonomy used for this use case.)
• Talent Sourcing from Alternative Candidate Pools for Employers: In cases where employers are seeking to increase the number of viable candidates for their positions, AdeptID recommends occupations with adjacent skills. This use case is satisfied using Recommend Source Occupations. (O*NET 2019 Simplified is the occupation taxonomy used for this use case.)
• Occupation Classification, Data Enrichment, and Data Analysis for Analysts: In cases where developers wish to categorize job postings, work experience, and/or append additional metadata to those job objects, AdeptID can classify the occupation of the job or work experience into a standard category. These use cases are satisfied using the Occupation Classification and Occupation Metadata. (O*NET 2019 is typically used for this use case. O*NET 2019 Simplified may also be used.)
• Skills Inference for Shortlisting Candidate for Jobs: AdeptID infers the skills that a candidate has developed in a role or that a role requires based on the skill requirements for other jobs with the same or similar titles. These use cases are satisfied using Evaluate Candidates and Evaluate Jobs. (O*NET 2019 Extended, AdeptID’s internal occupation taxonomy is used for this use case.)

Occupation Taxonomy Details

AdeptID’s occupation taxonomies are based on the O*NET occupational taxonomy, sponsored by the US Department of Labor. We use the current version of the O*NET taxonomy, O*NET 2019 verbatim, and also modify the taxonomy in order to support specific use cases. AdeptID’s endpoints which output occupations - Occupation Classification, Recommend Source Jobs, and Recommend Destination jobs - allow developers to specify whether to output data in O*NET 2019 and O*NET 2019 Simplified, our two public occupation taxonomies.

O*NET 2019

O*NET 2019 Simplified

Canonical Values

A list of the value in AdeptID's occupation taxonomies and general information about occupation names and groupings can be accessed here.