Job Title Prediction and Recommendation System for IT Professionals

In the current era of globalization, finding and searching for suitable jobs heavily relies on manual systems, which often prove to be time-consuming and fail to deliver optimal outcomes. Addressing these challenges, we present an advanced job prediction system called the Job Title Prediction and Recommendation System (JoTPaRS). Leveraging machine learning techniques, JoTPaRS offers personalized multiple job title suggestions and salary range estimations based on the user's knowledge, requirements, job description, and experience. Our research focuses on developing a robust prediction system that caters to the needs of job seekers, recruiters, and HR departments. Compared to existing approaches in the field, our proposed system demonstrates remarkable performance, achieving an accuracy score of 95.63 %. In contrast, alternative methods exhibit accuracy ranges between 60% and 85% when predicting and determining job titles based on textual job descriptions. Ad-ditionally, we incorporate experience-based salary ranges for each predicted title into our recommendations to ensure accurate and reliable suggestions for users. In alignment with the paradigm of Industry 5.0 and the principles of Sustainable Technology, our research offers a pivotal step towards enhancing the efficiency and sustainability of the modern workforce, fostering a more dynamic and eco-conscious employment landscape.