Analysis of the Employee Satisfaction Level Using Methods of Machine Learning

Both government and private companies have been concerned with the problem of employee turnover for decades. High turnover rate leads to many undesirable consequences. Employee satisfaction analysis is a key method of solving this problem. With the continuous growth of data volumes, most analytical processes cannot be performed manually. However, the widespread and constant development of computer technologies allows to automate many processes, as well as to create more complicated and efficient models. This work considers the use of modern methods of machine learning to analyze the level of employee satisfaction. The ultimate goal of the study is to analyze existing developments in this area and create a predictive model that will be able to recognize employees planning to leave, as well as identify the reasons that led to this. The anticipated results can be used in the future by different companies to control employee turnover.