Independent Researcher History And Philosophy Of Machine Learning, AI And Statistics
Seattle, Washington, United States
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Summary
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Roald Severtson is an independent researcher and technical writer who combines seven years in AI/ML product documentation with decades of applied mathematics, hydrogeology, and environmental modeling experience. He has authored developer-facing content for AWS SageMaker and Braket, translating complex topics like AutoML, bias diagnosis, and quantum computing into practical guidance for data scientists. With formal training spanning Oxford modern history to graduate work in environmental engineering and conceptual foundations of science, he uniquely bridges history and philosophy of science with hands-on statistical and modeling practice. His background includes senior roles at Microsoft and Amazon and earlier leadership in forensic hydrogeology and groundwater remediation, reflecting a career that moves fluidly between field science and cloud-native ML. Notably, he frames technical problems through historiographical and philosophical lenses—examining the interplay between theory and data—which informs both his research and documentation. Based in Seattle, he brings a rare mix of quantitative rigor, narrative clarity, and environmental ethics to AI and statistics discourse.
7 years of coding experience
21 years of employment as a software developer
Graduate work, Environmental Engineering: Specialized in Modeling and Hydrogeology, Graduate work, Environmental Engineering: Specialized in Modeling and Hydrogeology at University of Washington
BA/MA, Modern History, BA/MA, Modern History at University of Oxford
BA and BS, awarded summa cum lauda, Four Majors: Mathematics, Physics, Chemistry, and Philosophy, BA and BS, awarded summa cum lauda, Four Majors: Mathematics, Physics, Chemistry, and Philosophy at University of Puget Sound
Masters, Conceptual Foundations of Science, Masters, Conceptual Foundations of Science at University of Chicago
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Roald Severtson - Independent Researcher History And Philosophy Of Machine Learning, AI And Statistics