Rigorous mathematics for quantitative finance
Mathematics graduate (BSc, Leibniz University Hannover) now pursuing an MSc in Mathematics with a focus on quantitative finance at the University of Vienna. I build derivatives pricing engines, calibrate yield curve models, and implement vol surface interpolation from real market data — from first principles.
01About
I hold a BSc in Mathematics from Leibniz University Hannover, specialising in partial differential equations, numerical analysis, and stochastic analysis. My thesis, "A stochastic PDE system for chemotaxis," was graded 1.0.
Alongside my studies, I build quantitative tools from scratch — pricing engines in Python with no black-box dependencies, yield curve models calibrated on real Bundesbank data, and vol surface interpolation using the AAA algorithm on live SPX options. Between November 2025 and September 2026 I worked in academic assistant and research roles at the Institute of Applied Mathematics (LUH) and completed a research internship at the Zuse Institute Berlin (ZIB).
I'm now pursuing a Master's in Mathematics with a focus on quantitative finance at the University of Vienna, started in 2026.
02Selected Work
Derivatives pricing
Options Pricing Engine
Analytical and semi-analytical pricing for European vanilla and barrier options. Implements Black-Scholes with full Greeks, implied volatility inversion, and Heston stochastic volatility — every formula derived from first principles.
PythonNumPySciPyHeston
Fixed income
Yield Curve Fitting
Calibration of Nelson-Siegel (1987) and Svensson (1994) yield curve models on real Bundesbank spot rate data. Pure SciPy/NumPy — no QuantLib, no sklearn.
PythonSciPyNelson-SiegelSvensson
Volatility modelling
Vol Surface Interpolation
Interpolation of implied volatility surfaces from real SPX options data using the AAA algorithm. Includes no-arbitrage verification via calendar spread and butterfly spread checks.
PythonAAA AlgorithmSPX DataArbitrage-Free
03Academic & Professional
Graduate studies in mathematics with a focus on quantitative finance, building on a PDE and stochastic analysis background from my Bachelor's degree.
Assisting in undergraduate analysis courses, grading assignments and correcting exams. Tutoring and grading for economics students.
Independent research on adaptive sampling strategies for AAA rational approximation of expensive black-box functions, with applications to electromagnetic transmission (Maxwell equations, JCMwave) and implied volatility surfaces (Heston, SABR).
Creation of mathematical problems and competition materials for workshops and student internships.
Specialisation in partial differential equations and numerical analysis. Core coursework: Functional Analysis, Numerical Methods for PDEs, Financial Mathematics, Stochastics. Completed 213 ECTS in total (180 required), overall GPA 1.3. Thesis: "A stochastic PDE system for chemotaxis" (grade 1.0) — download PDF.
Completed 90+ ECTS of advanced mathematics coursework while in high school, credited toward the BSc degree.
Experimental physics and quantitative data analysis. Laboratory work with measurement systems and statistical evaluation of experimental results.
04Technical Stack
Mathematics
- Partial Differential Equations
- Stochastic Calculus
- Numerical Analysis
- Functional Analysis
- Measure Theory
Programming
- Python
- MATLAB
- LaTeX
- NumPy / SciPy / Pandas
- Matplotlib / Plotly
- Git / GitHub
Quantitative Finance
- Derivatives Pricing
- Vol Surface Calibration
- Yield Curve Modelling
- Greeks & Risk Metrics
- Backtesting Frameworks
- QuantLib / Bloomberg
05Get in Touch
Open to conversations about quantitative finance and research collaborations. Best reached via the form below or LinkedIn.