Modeling Compensation of Data Science Professionals in BRIC Nations

Abstract

This paper proposes a model for predicting the compensation of data science professionals in BRIC nations based on the worldwide Data Science Survey conducted by Kaggle in 2017. In this paper, we have used the Rosling’s approach to adjust the compensation amount in BRIC currencies with respect to Purchasing Power Parity (PPP) units. Exploratory data analysis is used to identify the factors that influence the compensation amount, and an XGBoost algorithm is employed to predict the compensation. We evaluate the performance of the model by generating the Root Mean Squared Log Error (RMSLE) score. The results indicate a robust prediction using the XGBoost algorithm.