Ralph Rudd
Senior Risk Specialist at Danske Bank
Copenhagen, Capital Region of Denmark
Summary
👤
Senior🎓
Top SchoolRalph Rudd is a Senior Risk Specialist and quantitative finance researcher with a PhD and over a decade of experience applying numerical methods and machine learning to financial risk and model validation. He has held faculty roles teaching numerical methods and quantitative risk at top programs and consulted on ML model validation aligned with the EU AI Act, authoring an internal framework for production use. His engineering contributions include implementing and refactoring finite-difference solvers (Black–Scholes Theta, CEV) in an established mathematical finance library, reflecting deep practical expertise in option pricing and numerical PDEs. Based in Copenhagen, he blends academia, banking, and hands-on consulting with a creative bent—coaching Brazilian jiu-jitsu and experimenting with game development—bringing disciplined problem-solving and multidisciplinary communication to complex risk problems.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Quantitative Finance, Doctor of Philosophy - PhD, Quantitative Finance at University of Cape TownBSc Honours, Applied Mathematics, Cum Laude, BSc Honours, Applied Mathematics, Cum Laude at University of StellenboschOnline Short Course, Digital Photography, Online Short Course, Digital Photography at GetSmarter
Danish, Afrikaans, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
simulation10
javas10
difference10
finite-difference10
math10
modeling10
java10
quantitative-finance10
simulations7
monte-carlo4
Programming languages (3)
Github contributions (5)
finmath/finmath-lib
May 2018 - Nov 2018
Mathematical Finance Library: Algorithms and methodologies related to mathematical finance.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:13 commits, 10 pushes in 5 months
Contributions summary:Ralph's primary focus was on implementing and refactoring finite difference methods within the mathematical finance library. They developed a Black-Scholes Theta solver and a CEV model, indicating expertise in numerical methods for option pricing. Furthermore, the user integrated and tested these methods, demonstrating a strong understanding of the underlying financial models and their practical application within the library. The user also refactored and improved existing code related to these methods.
finmath-libmonte-carlo-simulationjavasimulationmathematical-modelling
IkeThermite/pymathfi
Nov 2019 - Jul 2022
A small collection of math finance experiments in python.
Contributions:19 commits, 2 PRs, 23 pushes in 2 years 7 months
python
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