Philipp Schädle is a founder and data & AI engineer with eight years of cross-disciplinary experience turning complex scientific and industrial data into actionable, production-ready systems. He blends a strong academic foundation (PhD from ETH Zurich) in numerical modeling and statistics with hands-on software engineering—C++, Python, Java—and automation of data pipelines for safety-critical domains like nuclear repository assessments. At ENSI he combined simulation, risk modeling and stakeholder coordination, and now runs a boutique practice building analytics architectures, ML/LLM prototypes and decision-support tools. Philipp’s background in high-performance numerical methods and international collaboration means he excels at translating rigorous research into practical, auditable solutions for organisations exploring AI adoption. An understated strength is his fluency across the full lifecycle—from CI/CD and testing for numerical code to advisory work on data infrastructure and governance.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Institute of Geophysics, ETH Zürich, Switzerland , Doctor of Philosophy - PhD, Institute of Geophysics, ETH Zürich, Switzerland at ETH Zürich
Diplom-Ingenieur (M.Sc.) Environmental Engineering, Umweltschutztechnik, Diplom-Ingenieur (M.Sc.) Environmental Engineering, Umweltschutztechnik at University of Stuttgart
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