Predictive Salary Modelling: Leveraging Data Science Skills and Machine Learning for Accurate Forecasting

In approaching predictive salary modeling, this article identified important job positions and skills in the data science business environment. They show the need for a model that would allow employers to calculate the required starting salary while considering sectors, Python known languages, SQL, and ML. It also analyzes linear regression models, Random Forests, and neural network point of view about salary prediction. Analyzing the findings, it is proved that skill-based salary models should be further developed to meet industry requirements, advise students, and support employers. We have applied various models as follows with random forest performing the best giving out an R2 score of 0.971. The ideas for building faultless, precision, and skill-based salary estimation models are presented to the readers at the end of the article.