- Implemented algorithms for approximation of π using Python
Brief explanation:
Master’s student in Mathematical Data Science with a solid background in mathematics and insurance. Completed specialized courses in Life Insurance and Non-Life Insurance Mathematics under Prof. Michael Fröhlich. Interested in applying statistical and computational methods in reinsurance and risk analysis.
Working as a member of the University LATEX group and doing several projects, collaboration, and leading for solving problems in computational methods at different projects (LATEX, C++).
- Implemented algorithms for approximation of π using Python
- Developed an Automatic Differentiation framework in Python to compute derivatives of complex functions, applied in optimization and machine learning contexts
Available for a student position (up to 80h/Month)
Highly committed and reliable; my dedication to responsibilities led to a promotion from cashier to shift leader at KFC after a short period.