CREATION OF SALARY PREDICTION SYSTEM

Abstract

Salary prediction is an important problem for many organizations as it directly affects the financial wellbeing of employees and the competitiveness of the organization. Accurately predicting employee salaries enables organizations to make informed decisions about compensation and benefits packages, leading to a more equitable distribution of compensation, improved organizational performance and increased employee satisfaction. In today’s highly competitive job market, accurate salary prediction is increasingly important as organizations seek to attract and retain the best talent, maintain a motivated and productive workforce, and stay ahead of the competition. The prediction of salaries for employees can be challenging as it requires taking into account a wide range of factors including years of experience, education, skills, job responsibilities, industry trends and more. Salary prediction systems can also help to identify and eliminate any potential salary disparities between different groups of employees. By providing a more objective and data-driven approach to determining salaries, these systems can help to promote fairness and equity in the workplace. Additionally, salary prediction systems can be useful for companies to budget and plan their finances, by having a better understanding of the potential salary range for a given job, the company can budget accordingly. The practical value of this work is the salary prediction system which can provide valuable insights and help to make more informed decisions about compensation, which can benefit both employers and employees Moreover, with the advent of machine learning and artificial intelligence, it has become possible to develop sophisticated algorithms and models to analyze vast amounts of data and make accurate salary predictions. These systems use deep learning techniques, such as neural networks, to analyze large amounts of data and predict salaries based on a wide range of factors. This technology is becoming increasingly widespread and is poised to play a major role in the future of human resources and compensation decision-making.