Dino De Raad is an applied mathematician and data scientist with eight years of experience translating complex problems into practical, reproducible solutions for healthcare and Fortune 500 technology clients. He has built novel algorithms for financial target-setting, developed a customer-focused maturity index with logistical staffing plans, and produced interpretable time-series and ML models used in senior decision-making. Dino pairs academic rigor—a MA in Statistics and ongoing graduate work in Applied Data Science—with hands-on lab and research experience in biomedical imaging and diagnostic techniques. A practiced educator, he has designed and led machine learning curricula for cohorts of 40–50 professionals and currently teaches as adjunct faculty in Seattle. Colleagues note his focus on numerical stability, interpretability, and documentation that enables cross-team replication and continuous improvement.
8 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree, Applied Mathematics: Scientific and Numerical Algorithms, Bachelor’s Degree, Applied Mathematics: Scientific and Numerical Algorithms at University of Washington
Master's degree, Applied Data Science, Master's degree, Applied Data Science at University of Michigan
Master of Arts, Statistics, Master of Arts, Statistics at University of Rochester School of Medicine and Dentistry
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Dino De Raad - Adjunct Faculty at North Seattle College