Job Role Prediction System

The job outlook growth in recent years has been growing constantly as per the market requirements. Specifically in the areas of those where there is a higher necessity of specialized, trained and skilled professionals. Often not all the seekers get their desired jobs based on their skills. This is a cause of concern as it might lead to a lot of indifference between the seekers. So, a Web Application could be developed so that an employment-availability or employee-availability search engine can be used in this process. This Web Application can be used by employers and employees. The Application makes use of Machine Learning (ML) and Neural Networks in order to predict whether a candidate is eligible for a given job based on a set of hyper parameters. These parameters can be their major, Grade Point Average (GPA), Co-Curricular activities and Internships. The Parameters mentioned here are relevant to a University student. In the testing process we different models are worked with of which are Decision Trees, Support Vector Machine, Sequential neural network and XgBoost. With the XGBoost giving the highest accuracy of 93.02%. This study is primarily concentrating on freshly graduated computer science engineers, but it can be extrapolated to professionals of other domains.