AI-Driven Talent Matching Predicting Employee Retention Through Candidate Attribute Analysis

Yasir Imtiaz Shami, Tosin Adewumi

Keywords: AI, talent prediction, HR

Abstract: This study presents an AI-driven talent matching framework that combines semantic similarity with retention-aware modeling. The system uses transformer-based embeddings to match candidates and jobs, while also predicting retention through psychometric traits, employment history, and education. The results show that semantic matching alone provides strong rankings, but adding retention scoring improves shortlist quality.

Serve As Reviewer: ~Tosin_Adewumi1

Submission Number: 22