Tech Stack: Python, Bash, SQL, Javascript/Typescript, Java

Expert’s cases:

1. Researching on Physics-based DL and Computational Finance

2. Within the Computational Finance project, worked together with the KIT Chair of Financial Economics and Risk Management in order to apply Machine Learning to perform time series forecasting on a large financial derivatives dataset using models such as Transformers

3. Development of ChatBots and SkillBots for Swiss authorities

4. Development of classic Machine Learning as well as Deep Reinforcement Learning models for both POC as well as production systems

5. Developed and enhanced two PDE-based Deep Learning models for continuous sensor value interpolation and calibration using TensorFlow 1 and PyTorch. Focused on the air quality use case and PDEs which describe the distribution of particulate matter within air

6. Research paper based on results is currently in progress

7. Development and Implementation of a Machine Learning platform with Blockchain binding and its end-to-end infrastructure to perform predictive maintenance and dynamic leasing for a research project supported by the German Federal Ministry of Education and Research

8. Best Data Scientist in the “Digital Shapers 2020” competition from McKinsey. More than 1000 people applied for the competition and went through 3 rounds in the application process. 30 people were selected to participate in the competition and distributed into 5 teams. Our team took second place and I received a personal prize for my role as “Best Data Scientist”. The jury consisted of executives from various international companies, including the CEO of McKinsey Germany & Austria at that time