SYSTEMS AND METHODS TO IDENTIFY RESUMES FOR JOB PIPELINES BASED ON SCORING ALGORITHMS

1 . A computer-implemented method comprising:

determining, by a computing system, a first score generated by a first scoring algorithm that determines a degree to which a resume is matched to a job pipeline of an organization;

determining, by the computing system, a second score generated by a second scoring algorithm that determines a degree to which the resume is matched to the job pipeline; and

processing, by the computing system, the first score and the second score to generate an aggregate score.

2 . The computer-implemented method of claim 1 , wherein the processing the first score and the second score comprises:

generating a first weight associated with the first scoring algorithm; and

generating a second weight associated with the second scoring algorithm.

3 . The computer-implemented method of claim 2 , wherein the first weight and the second weight are based at least in part on associated claimable resume percentages resulting from a manual review process of resumes regarding the accuracy of the first scoring algorithm and the second scoring algorithm.

4 . The computer-implemented method of claim 2 , wherein the first weight and the second weight are developed using a linear regression technique based on a machine learning model.

5 . The computer-implemented method of claim 2 , wherein the processing the first score and the second score comprises:

applying the first weight to the first score to generate a first weighted score; and

applying the second weight to the second score to generate a second weighted score.

6 . The computer-implemented method of claim 5 , wherein the processing the first score and the second score comprises:

combining the first weighted score and the second weighted score to generate a relevance score.

7 . The computer-implemented method of claim 6 , wherein the processing the first score and the second score comprises:

multiplying the relevance score and a goodness score to generate the aggregate score, the goodness score indicating suitability of a job candidate associated with the resume with the organization without regard to the job pipeline.

8 . The computer-implemented method of claim 1 , further comprising:

automatically providing to the recruiter at a regular interval an identification of job candidates associated with resumes most suited to the job pipeline based on aggregate scores of the resumes.

9 . The computer-implemented method of claim 8 , further comprising:

in response to selection by the recruiter of a particular job candidate, providing detailed information about the job candidate.

10 . The computer-implemented method of claim 1 , further comprising:

determining one or more job pipelines best matched with a resume uploaded by the recruiter.

11 . A system comprising:

at least one processor; and

a memory storing instructions that, when executed by the at least one processor, cause the system to perform:

determining a first score generated by a first scoring algorithm that determines a degree to which a resume is matched to a job pipeline of an organization;

determining a second score generated by a second scoring algorithm that determines a degree to which the resume is matched to the job pipeline; and

processing the first score and the second score to generate an aggregate score.

12 . The system of claim 11 , wherein the processing the first score and the second score comprises:

generating a first weight associated with the first scoring algorithm; and

generating a second weight associated with the second scoring algorithm.

13 . The system of claim 12 , wherein the first weight and the second weight are based at least in part on associated claimable resume percentages resulting from a manual review process of resumes regarding the accuracy of the first scoring algorithm and the second scoring algorithm.

14 . The system of claim 12 , wherein the first weight and the second weight are developed using a linear regression technique based on a machine learning model.

15 . The system of claim 12 , wherein the processing the first score and the second score comprises:

applying the first weight to the first score to generate a first weighted score; and

applying the second weight to the second score to generate a second weighted score.

16 . A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:

determining a first score generated by a first scoring algorithm that determines a degree to which a resume is matched to a job pipeline of an organization;

determining a second score generated by a second scoring algorithm that determines a degree to which the resume is matched to the job pipeline; and

processing the first score and the second score to generate an aggregate score.

17 . The non-transitory computer-readable storage medium of claim 16 , wherein the processing the first score and the second score comprises:

generating a first weight associated with the first scoring algorithm; and

generating a second weight associated with the second scoring algorithm.

18 . The non-transitory computer-readable storage medium of claim 17 , wherein the first weight and the second weight are based at least in part on associated claimable resume percentages resulting from a manual review process of resumes regarding the accuracy of the first scoring algorithm and the second scoring algorithm.

19 . The non-transitory computer-readable storage medium of claim 17 , wherein the first weight and the second weight are developed using a linear regression technique based on a machine learning model.

20 . The non-transitory computer-readable storage medium of claim 17 , wherein the processing the first score and the second score comprises:

applying the first weight to the first score to generate a first weighted score; and

applying the second weight to the second score to generate a second weighted score.