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3.3. Salary validation
3.3.1.
Purpose
The salary-matching feature’s purpose is to ensure that a user's salary expectations align with the salary range offered for a job, based on the salary expectations of the candidate and the proposed salary on the job.
3.3.2.
Data
3.3.2.1.
Candidates
The data for this factor is provided by the candidates themselves. Candidates can input and update their salary expectations during the onboarding process of the platform, in the edit section while viewing their profiles, or through interactions with the recruiter bot. Lastly, salaries can be modified for specific job applications to be lower or higher just for those in particular.
3.3.2.2.
Talent seekers
Talent seekers can outline their budgeted salary range in the job post during onboarding or while editing the job.
3.3.3.
Data validation
To make sure jobs posted on our platform provide value to our job seekers and to make sure talent seekers have the best chance of finding the right talent, we do an automated market analysis for every job posted on the platform. We provide knowledge on how high salary expectations of candidates are based on all attributes of the job post.
3.3.4.
Algorithm validation
- Daily and weekly metrics
- Editorial reviews
- Direct feedback from talent seekers
- Direct feedback from candidates
3.3.5.
Description
Initially, we convert the salary of the candidates and the job to USD using a currency conversion library. Then we normalize the salary to an hourly rate. In most cases, the periodicity is the same but we provide the option of specifying hourly, monthly and yearly compensations. Some job posts might be unpaid. In this case, only candidates with the preference “open to unpaid jobs” or with a salary expectation of 0 will be matched.
There are multiple ways of configuring the salary of a job and each one has a specified logic to be handled separately.
3.3.5.1.
Fixed salary
The job’s salary is divided by the candidate's salary with a maximum score of 1.
3.3.5.2.
Salary range
The job’s maximum salary is divided by the expected salary of the candidate with a maximum of 1.
3.3.5.3.
To be agreed upon
We match everyone equally with a score of 1.
Extras:
- Equity
- Commissions
- Bonuses
- Health insurance
- Other
3.3.6.
Mathematical description
3.3.7.
Uncertainty
Uncertainty in this factor is defined by the range of the job compensation. If the compensation of a job has a range we assume the upper bound for defining if we want to match a candidate but the lower bound defines the uncertainty for if that’s actually a match or not.
Fair artificial intelligence.
We’re committed to it.
