Summary
Daniel Bischof is a quantitative investment analyst and mathematician with 10 years’ experience designing valuation and risk models for derivatives, clearing, and asset management. He combines deep theoretical expertise in stochastic methods, extreme value theory and PDE solvers with hands-on engineering—building QuantLib-based engines, high-availability Python reporting systems, and performant numerical solvers (FEM/FVM), with additional experience in Rust and SQL. His work spans margin methodology and crypto-derivative research at Eurex, NAV-critical production valuation at Allianz GI, and model development for bespoke auto-callable structures, demonstrating an ability to translate research into time-critical production systems. Comfortable leading cross-functional projects, he has also run company-wide Python training and set up prototyping environments, showing a knack for tooling and team enablement beyond pure research. Based in Hamburg, he pairs academic rigor from TU Darmstadt and EPFL with pragmatic software design, often focusing on making complex stochastic models both fast and auditable in production.
10 years of coding experience
3 years of employment as a software developer
Technischen Universität Darmstadt
Graduate Research Project Mathematical Statistics and Probability, Graduate Research Project Mathematical Statistics and Probability at EPFL
Hong Kong University of Science and Technology (HKUST)
English, German, French, Chinese