Employee Attrition Prediction Model

The rapid digital transformation of workplaces has shifted Human Resource Management (HRM) from traditional administrative tasks to data-driven, strategic operations. This paper presents the design and development of an AI-Driven HR Hub that leverages artificial intelligence, machine learning, and cloud integration to address critical HR challenges such as resume parsing, recruitment, and employee attrition prediction. Unlike conventional HR systems that rely heavily on manual interventions, the proposed solution automates candidate evaluation, extracts structured insights from unstructured resumes using Natural Language Processing (NLP), and applies predictive modelling through Random Forest classifiers to assess attrition risks. The system also incorporates Firebase for secure cloud storage and Flask for building a scalable, user-friendly web application. A series of experiments validate the efficiency of the proposed system in reducing recruitment time, improving decision accuracy, and enhancing employee retention strategies. This research demonstrates the potential of AI in revolutionizing HR processes by offering predictive intelligence, operational scalability, and data transparency.