About me
I am Hendrik, a mathematician turned actuary with an academic background in numerical mathematics and scientific computing. I earned my PhD from Leibniz University Hannover researching reduced-order modeling for physical systems such as fluid dynamics and porous media. There, I developed data-driven numerical models designed to minimize computational effort by dynamically adapting to new parametric conditions.
After my PhD in 2024, I transitioned into the insurance industry as a reserving actuary, and I am currently pursuing qualification as a DAV actuary. My work can be summarized by this credo:
Actuaries write code.1 As modern actuaries, we move beyond spreadsheets and proprietary black boxes. We build reliable, open, and transparent systems - tools that scale and last.
Outside of work, I am passionate about programming, investing, personal development, and Bitcoin (not crypto). I feel most comfortable using Python and AI to tackle challenges I encounter both at work and beyond, and I love building automations that make my life easier (like building this website; thanks opencode).
My Resume
Full background and publications in one PDF. Download CV (PDF)
Work Experience
- 2024-Present: Reserving Actuary, HDI Global Specialty SE
- 2022-2023: Research Visitor, ENS Paris-Saclay
- 2021-2024: Doctoral Candidate, Leibniz Universität Hannover
- 2017-2021: Student Assistant, Technische Universität Hamburg
Education
- 2025-Present: Actuary DAV, Deutsche Aktuarsvereinigung
- 2021-2024: PhD (Dr. rer. nat.), Mathematics, Leibniz Universität Hannover
- 2019-2021: M.Sc. Industrial Mathematics, University of Hamburg
- 2016-2019: B.Sc. Technomathematics, Technische Universität Hamburg
Academic Contributions
Selected papers and conferences are listed on the academic contributions page.
Current Projects
Work
- Attritional/large-loss splitting approach for reserving
- Finding optimal large-loss threshold
- Attritional reserving using
chainladder-python - Large-loss projections based on frequency-severity analysis using GLMs and Monte Carlo simulations
- Coordinating resegmentation of reserving segments
- Building an automated mapping approach that reflects the new business logic
- Building new analysis tools within
pythonandchainladder-pythonto support mapping decisions
Personal
chainladder-python- Familiarizing myself with, using, and contributing to this fantastic open-source reserving library
- AI-assisted math tutoring
- Agentic approach using
opencodealongsidelatexandmarkdown(Obsidian) to create student-tailored lessons and exercises - (Not yet open source)
- Agentic approach using
- Sharpen-the-saw projects
Contact
Email me at [email protected].
Paraphrased from Eric Hughes’ A Cypherpunk’s Manifest ↩︎