Pierre Wüthrich is a Senior Data Scientist based in Zurich with 8 years of experience applying deep learning, graph neural networks, Bayesian optimization and XAI to real-world problems across consulting and industry. Trained as a chemical engineer at EPFL and the University of Tokyo, he translates domain knowledge from chemistry and physical systems into production-ready ML solutions, from PyTorch model pipelines to federated learning setups. At Elix and DeepX he led technical projects and R&D that produced a NeurIPS workshop paper on interpretable molecular optimization and delivered DL controllers for autonomous heavy machinery. Now at BCG X/BCG he pairs consulting impact with hands-on engineering, bridging research-grade methods and client-facing deployment. An unusual strength is his cross-cultural background and experience shipping both research contributions and commercialized, end-to-end ML systems.
8 years of coding experience
6 years of employment as a software developer
University of Tokyo
Bachelor's degree, Chemistry and Chemical Engineering, Bachelor's degree, Chemistry and Chemical Engineering at Ecole polytechnique fédérale de Lausanne
Exchange Year, Chemical Engineering, Exchange Year, Chemical Engineering at ETH Zürich
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