Data Model Overview

Our matching endpoints evaluate the fit between candidates and jobs or candidates and occupations and describe the fit as a match.

Our matching model uses the following entities:

Candidate describes a job applicant, including their work experience, education, skills, and industry certifications. Customers can enhance candidate profiles with custom features such as assessment results, internship descriptions, and education achievements.

Job describes a job opening. Relevant fields include the job title, employer, industry, skills, certifications, and educational credentials requested.

Occupation describes a category of jobs rather than a specific job. Examples of occupations include electrical engineers, marketing managers, and machinists. Occupations are used when:

Job seekers are exploring career transitions rather than seeking specific roles.
Employers are seeking to increase the number of viable candidates for open positions.
Training providers want to show their learners prospective career pathways

Available data about occupations includes typical skill and credential requirements, typical salaries, demographics and volume of workers in the role, and employer demand.

Match assesses the fit between a candidate and a job or an occupation and explains the rationale for that assessment. It includes the following elements:

Match score
Attribute scores for work experience, skills, and education
Skills report with skill gaps and overlaps
Narrative explanation of the match quality

Other Entities in our Data Model: These entities are nested in candidate, job and occupation entities described above.