Research Engineer in Statistical Modeling

Lorenz Gaertner is a Research Engineer / Applied Statistics Engineer with a physics background and strong Python/C++ skills. They specialize in building statistical methods, probabilistic models, and research software for technically challenging problems. Their experience includes developing a new statistical method used in multiple publications, creating open-source Python software for automated statistical analysis workflows, and contributing to widely used research-computing libraries in particle-physics research at LMU Munich. Their work bridges mathematical modelling and robust software development, focusing on transforming ambiguous inference problems into reusable tools, reproducible analyses, and clear technical explanations. They have presented technical work at international venues like CERN and PyHEP and have advised technical stakeholders in governmental and international contexts. Lorenz is seeking full-time Research Engineer / Applied Statistics Engineer roles, particularly those emphasizing rigorous inference and evaluation, with a strong interest in AI evals/safety, applied statistics, scientific computing, and technical strategy.