Moayad Alhejji

Leads advanced analytical initiatives supporting national-level operational decision-making.
• Build and apply time-series forecasting models to analyze trends and seasonality and predict national-level demand spikes and
crisis periods.
• Develop predictive and scoring modules to prioritize risks, signals, and operational attention at national scale.
• Apply machine learning techniques (e.g., clustering, anomaly detection) to uncover patterns, outliers, and emerging risks.
• Implement Statistical Process Control (SPC) methods for healthcare operations to monitor system stability, detect abnormal
variation, and support early intervention.
• Design and maintain early-warning indicators combining forecasting, SPC, and anomaly detection to flag emerging national risks.
• Translate analytical outputs into decision thresholds and operational triggers for leadership and command-center teams.

• Built advanced analytics dashboards and reports to deliver actionable insights for operational monitoring and data-driven decision
making
• Developed and enhanced KPIs to better reflect operational performance and support informed decision-making
• Built data pipelines to extract, transform, and load data from multiple sources for reporting and analytics
• Produced operational and analytical reports translating data into clear insights for routine performance review
• Performed data extraction, transformation, and analysis using SQL, Python, and Excel, ensuring data quality and metric
consistency

At Muthlthat, Moayad led the UI/UX design team to craft intuitive and visually appealing digital experiences. In parallel, he was
responsible for structuring and organizing backend data systems to support future analytics and data-driven solutions, ensuring a
seamless integration between design, functionality, and long-term business intelligence.
As a front-end developer, Moayad was focused on transforming UI designs into fully responsive, clean, and easy to maintain web
interfaces, utilizing advanced coding techniques for optimal user experience and efficiency.