Forecasting trending jobs based on a Saudi's technological mega-corporation: STC Group

Abstract In a rapidly changing world, recognizing change early enables successful adaptation. COVID-19 has challenged public and private sectors to shift towards a contactless environment, necessitating significant investment in technology and digital transformation. Wise countries and corporations have proactively launched digitization initiatives. This shift will inevitably alter job titles, positions, and required skills in the near future. To explore the relationship between labor markets and technological demands, we studied employment at STC Group in Saudi Arabia, the largest telecommunications corporation in the Middle East according to Bloomberg. Analyzing STC's current job positions offers insights into future technological job market needs. This work gathers data on STC employees from LinkedIn and analyzes it to identify gaps, impacts, and forecast job trends for the next eight years. We believe this analysis provides a clear view of Saudi Arabia’s labor market trends, with implications for global trends. Additionally, this work develops a generic framework for data scientists using techniques like data engineering, preparation, and modeling. Two clustering algorithms were developed: K-Means with the Elbow method and Latent Dirichlet Allocation for Topic Modeling. Forecasting algorithms include ARIMA and Regression Prediction based on Time Series. Detailed, promising results reflect current and future market needs.