Torre’s Job-Matching Model | Language fluency validation

3.2. Language fluency validation

3.2.1.

Purpose

The language-fluency feature’s purpose is to validate if a user is able to perform at the required level of the job considering languages and fluencies on their profile.

3.2.2.

Data

3.2.2.1.

Candidates

The data for this factor is captured by the candidates themselves. The candidates are able to validate their languages and fluencies in the onboarding process of the platform, in the edit section while viewing their genomes, through the recruiter bot. Also, we automatically detect languages based on a user’s location/IP if they don’t provide us with a language themselves.

3.2.2.2.

Talent seekers

Talent seekers can specify their requirements in the job post onboarding or while editing the job.

3.2.3.

Algorithm validation

Daily and weekly metrics
Editorial reviews
Direct feedback from talent seekers
Direct feedback from candidates

3.2.4.

Description

For every language in the job requirements, we check the user’s languages and their fluencies. If a user is missing a language or if their fluency is lower than the job requirements, we filter the user from the suggestions and the user will score 0 for this factor.

3.2.5.

Mathematical description

Let:

L be the set of languages in the job requirements.
F_u(l) U be the set of languages the user knows.
F_j(l) be the fluency level of the user in language.
l be the fluency level required for language l in the job requirements

3.2.6.

Uncertainty

Uncertainty factors of this feature are in “missing languages only”. When a language is missing from the candidate’s skillset we don’t assume that the person doesn't have it but instead, we let the candidate and talent seeker know that we have some missing information about the user. This is then reflected in the score as an uncertainty range.