I am a founder and a data science engineer with a Master of Research in data science from CentraleSupelec, one of the top engineering schools in France. I have a strong background in machine learning, data visualization, and statistical modeling, as well as proficiency in Python, R, C#, and NoSQL.In my previous roles, I have applied my data science skills to various domains, such as cellular network optimization, reinforcement learning, and time series generation. I have developed a benchmark of generative models for Nokia Bell Labs, published a paper in the VTC 2023 conference with two PhDs, and conducted mathematical research on load balancing policies for CNRS. I have also built an end-to-end backend for ML training automation with Docker, K3s, and KubeFlow.I am passionate about the intersection of technology and social impact, and I am eager to use my data science skills to make a positive difference in the world. I have participated in hackathons, such as Hack4Good and Data for Good, where I have worked on projects related to health, education, and sustainability. In my free time, I enjoy tinkering with new data science tools, exploring the outdoors, and learning new languages. I would love to connect with other data science enthusiasts and professionals who share my vision and values.