Yucong Hu is a Machine Learning Engineer with eight years of experience applying data science to business, climate, energy, and catastrophe risk problems, currently based in Toronto. A dual commerce and data science graduate (UVA McIntire, NYU CDS), he combines finance and analytics grounding with hands-on ML production experience—building deep-learning downscaling pipelines, LLM-driven legal risk prototypes, and scalable AWS/HPC deployments. His work at Verisk produced a CASMIL paper and a patent-worthy acceleration of climate data workflows, and he now contributes ML systems at Workday’s Agent Factory. Comfortable spanning research, product integration, and engineering, he brings a rare mix of domain fluency in risk modeling and pragmatic software delivery. An enthusiast for the intersections of digital transformation, politics, and Cantonese, he often blends technical rigor with cross-disciplinary thinking.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS), Commerce, Bachelor of Science (BS), Commerce at UVA McIntire School of Commerce
Master of Science - MS, Master of Science - MS at NYU Center for Data Science
Bachelor of Science (B.S.), Commerce, Bachelor of Science (B.S.), Commerce at University of Virginia
Contributions:8 pushes, 1 branch in 1 year 3 months
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