Exploring salary trends in data science, artificial intelligence, and machine learning: A comprehensive analysis

• Published in: AIP Conference Proceedings
• Main Author: Khan M.R.B.; Islam G.M.N.; Ng P.K.; Zainuddin A.A.; Lean C.P.; Al-Fattah J.; Basri A.B.; Kamarudin S.I.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203134255&doi=10.1063%2f5.0224376&partnerID=40&md5=6c96166e013e0e8d69e769227dc333d2

The rapid advancement of Data Science, Artificial Intelligence, and Machine Learning has created a dynamic job market. In line with other professions, salaries are provided as a means of compensating professionals for their work. However, it is evident from previous research that salary levels vary across different job fields, as each field contributes uniquely to its respective domain. The magnitude of this contribution directly influences the salary structure within a field. To shed light on this phenomenon, this data analysis project aims to examine the salaries dataset. The project's objective is to identify the factors that influence salary levels in these fields through comprehensive analysis. By exploring these trends, we can gain insights into the continued value of these fields in the coming years. © 2024 Author(s).