Suhail Mahmud is a Senior Catastrophe Risk Modeler and atmospheric data scientist with eight years of experience blending advanced machine learning and atmospheric physics to build and validate catastrophe models for hurricanes, floods, severe convective storms, and wildfire. Holding a PhD in Computational Science, he has moved seamlessly between academia and industry—from postdoctoral research in boundary layer and regional weather modeling to productionizing real-time weather data fusion and proprietary satellite ingestion. At firms like Karen Clark & Company, Tomorrow.io, and KatRisk he has driven ML-driven model development, operationalized novel data feeds, and communicated complex uncertainty to product and executive stakeholders. He is skilled in deep learning, reinforcement learning, and AWS-based deployments, and has a track record of turning research-grade methods into calibrated, business-ready risk products. Based in Natick, MA, Suhail pairs rigorous scientific benchmarking with practical engineering to meet evolving client needs. An uncommon strength is his end-to-end experience across satellite ingestion, nowcasting, and catastrophe-loss modeling—bridging raw atmospheric observations to insurer-facing risk metrics.
8 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computational Science, Doctor of Philosophy (Ph.D.) Computational Science at The University of Texas at El Paso
B.sc In Electrical & Electronics Engineering Electrical and Power Transmission Installers, B.sc In Electrical & Electronics Engineering Electrical and Power Transmission Installers at International Islamic University Chittagong
HSC Science, HSC Science at Rifles Public College
SSC Science, SSC Science at Motijheel Govt Boys High School
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