Employee Recruitment: Predicting Employee FIT and quality during pre-selection phase based on diverse applicant factors

Business Context

A recruitment agency wanted to upgrade its offering by helping companies auto select right fit and high yield candidates

Key Questions

  • What are the factors that drive the quality of an applicant?
  • What are the factors that drive yield?
  • How can data-driven predictive solution can be designed to select the candidates?

Impact Created

  • Reduced response time from 1 week to <24 hours for applicants
  • Saved approximately $200 k for a small scale recruiter with over 100 new Jobs every year
  • Ability to predict high quality applicant pool with 80% accuracy

Solution Design

  • Variable identification and selection
  • Solutioning
  • Output

Solutions Design:

Variable identification and selection:

  1. Applicant Demography
  2. Work experience
  3. Academics
  4. External Factors
  5. Application

Solutioning: Solutions Traits

  • Level Of Solution: At college
  • Time period: One year
  • Technique: AI and ML: Logistic Regression, SVM, Random forest
  • Validation: Out of Sample and Out of time

Results:

Tags: HR | IT