Med Hamza is a data scientist with nine years of experience combining strong mathematical and statistical foundations with practical machine learning and engineering skills, currently applying them at EY. He has built production-ready forecasting and fraud-detection models using tools like Python, R, SQL, XGBoost and stacking/blending ensembles, and has hands-on experience deploying data services from his developer background. Educated in data science and computer engineering, he bridges actuarial rigor with software implementation, making him comfortable across modeling, optimization and BI workflows. Known for being proactive, autonomous and sociable, he also brings presentation and team animation experience that helps translate technical results into business impact.
9 years of coding experience
2 years of employment as a software developer
Diplôme d'ingénieur, Computer Science, Diplôme d'ingénieur, Computer Science at Ecole Supérieure Privée d'Ingénierie et de Technologies - ESPRIT
Master 2 (M2) Data Science - Actuarial, Master 2 (M2) Data Science - Actuarial at Le Mans Université
MSEide is a Rapid Application Development IDE for platform independent rich GUI applications in the Pascal language. It comes with its own GUI toolkit called MSEgui. Binaries: https://github.com/mse-org/mseide-msegui/releases
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