Summary
Thomas Camminady is a Senior Data Scientist and applied mathematician with nine years of experience translating advanced numerical methods into production ML and signal-processing systems for sports and engineering applications. At Wahoo Fitness he builds and deploys time-series and sensor-fusion algorithms—bringing models from prototype to AWS-hosted APIs and embedded C for hardware sensors used by athletes worldwide. His background in kinetic theory and CFD research (PhD, KIT) informs pragmatic approaches to uncertainty quantification, reinforcement-learned solvers, and high-performance optimization on HPC stacks. Equally comfortable in Python data stacks (pandas, NumPy, Plotly, SQL) and low-level toolchains (Matlab → automated C code), he excels at cross-functional integration between cloud, frontend, and embedded teams. Colleagues rely on him for rapid prototyping that bridges rigorous theory and scalable productization—often surfacing non-obvious gains by applying scientific computing techniques to ML-driven product features.
9 years of coding experience
9 years of employment as a software developer
Doktor (Ph.D.), Applied Mathematics, Doktor (Ph.D.), Applied Mathematics at Karlsruhe Institute of Technology (KIT)
M.Sc., Computational Engineering Science, M.Sc., Computational Engineering Science at RWTH Aachen University
German, English, French