The Role of Data Science and Ai for Predicting the Decline of Professionals in the Recruitment Process : Augmenting Decision-Making in Human Resources Management

The scenario constituted by the emergence of fast-paced new technologies has been influencing the significant increase in the number of job opportunities in the Information Technology (IT) sector in recent years. Within this context, there are many challenges involved in the process of recruitment and selection for IT professionals, which are mainly regarded to the high decline rate of skilled workers. In this sense, it is very useful for companies to understand the aspects associated with the disengagement of these professionals in relation to the opportunities offered, as the selection process involves administrative decisions that may affect the performance of the organization as a whole. Thus, the hypothesis emerges that there are attributes of the selection process that are significant to predict the decline of a professional. Based on this hypothesis, this research aimed to identify the characteristics about the dropout of professionals in selective processes that are relevant to the prediction of professionals decline. More specifically, this hypothesis was investigated through an experimental research using processes of Data Science Lifecycle and Artificial Intelligence. For this purpose, we analyzed a dataset provided by an IT professional consulting company located in São Paulo - Brazil. Through machine learning techniques, the empirical results showed that it is possible to, not only predict professionals declination, but also to identify recruitment process features and their relevance in the process of job recruitment. In addition, this paper contributes with the models performance evaluation in real HR scenarios