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

• Main Authors: Khan, M. Reyasudin Basir, Islam, Gazi Md. Nurul, Ng, Poh Kiat, Zainuddin, Ahmad Anwar, Lean, Chong Peng, Al-Fattah, Jabbar, Basri, Atikah Balqis, Kamarudin, Saidatul Izyanie
• Format: Proceeding Paper
• Language: English; English
• Published: AIP Publishing 2024
• Subjects: T173.2 Technological change
• Online Access: http://irep.iium.edu.my/116637/7/116637_Exploring%20salary%20trends%20in%20data%20science.pdf; http://irep.iium.edu.my/116637/8/116637_Exploring%20salary%20trends%20in%20data%20science_Scopus.pdf; http://irep.iium.edu.my/116637/; http://doi.org/10.1063/5.0224376
• Institution: Universiti Islam Antarabangsa Malaysia

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.