THE SCIENCE OF HIRING : Predicting Personality through CV Parsing & Machine Learning

THE SCIENCE OF HIRING : Predicting Personality through CV Parsing & Machine Learning

Rishi Jain, Krishna Jaiswal, Pratham Jain, Tanay Jain,  Jainivas Anandhan, Jainil Vaidya, Supriya.S. Telsang

Department of Engineering, Sciences and Humanities (DESH) Vishwakarma Institute of Technology, Pune, 411037, Maharashtra, India

Abstract - Personality plays a crucial role in various aspects of human life, including career development, interpersonal relationships, and overall well-being. Traditional methods of assessing personality traits often rely on self-report questionnaires and subjective assessments, which can be biased and time-consuming. With the advancement of technology, there has been a growing interest in exploring alternative approaches to predict personality traits accurately and efficiently. This paper presents a novel approach to personality prediction using Curriculum Vitae (CV) analysis. The model for parsing the data utilizes Logistic Regression, a machine learning algorithm. Pyresparser, a tool, is employed to extract relevant information from a CV or resume. The proposed personality prediction system based on CV analysis has several potential applications. It can assist employers in the recruitment process by providing insights into the personality traits of job applicants, helping to identify suitable candidates for specific roles and improving the overall hiring decision- making process. Additionally, it can be used in career counselling and personal development settings, providing individuals with valuable feedback on their strengths, weaknesses, and potential areas for improvement.

Keywords— Curriculum Vitae(CV), Logistic Regression, Personality Prediction, Pyreparser, Resume.