Summary
Jonathan Hugenschmidt is a quantitative analyst and software-minded engineer with eight years of hands-on experience bridging machine learning, data engineering, and investment research. Currently at Mabanaft after quantitative roles at Munich Re and a machine learning/data engineering stint at Mensch Cologne Capital, he combines rigorous quantitative modeling with production-grade software skills. While completing an MS in Mechanical Engineering and Business Administration at RWTH Aachen and a semester at UC Davis, he also contributed to Nextcloud-related development at Verdigado, reflecting a practical open-source orientation. Based in Aachen, he brings a mix of industrial systems thinking from internships at BMW and WZL plus startup consulting experience, making him adept at turning complex data problems into deployable solutions. An early-career professional who moved quickly into quantitative finance roles, he stands out for pairing mechanical-engineering rigor with software delivery fluency.
8 years of coding experience
4 years of employment as a software developer
Semester abroad, Mechanical engineering, Semester abroad, Mechanical engineering at University of California, Davis
Master of Science - MS, Mechanical Engineering and Business Administration, Master of Science - MS, Mechanical Engineering and Business Administration at RWTH Aachen University
German, English, Norwegian, French