As a PhD Researcher at ÉTS, I collaborate with VMware on a cutting-edge project that aims to improve the Federated Learning (FL) model training costs in Open Radio Access Network (O-RAN) by considering users' mobility, network topology, and resource constraints. I have developed a novel optimization method, MCORANFed, that enhances the communication efficiency by 13% and reduces the resource usage cost by 19% compared to existing FL variants. I have also conducted convergence analysis and experimental validation of my method, and presented my work at the IEEE Wireless and Networking Conference 2022.My passion for data science and machine learning stems from my strong background in mathematics and edge computing. I have a master's degree in computer science and technology from Jawaharlal Nehru University, where I also worked as a research fellow on computation resource management in edge and fog computing. I have acquired multiple skills in statistical analysis, feature engineering, mathematical modeling, and data visualization using various tools and languages, such as R, SQL, MATLAB, Python, and Tableau. I have also earned a Google Data Analytics Professional Certificate and a Mitacs Project and Time Management Certificate to further enhance my competencies.I am motivated by the opportunity to apply my theoretical knowledge and practical skills to solve real-world problems that have a positive impact on society. I am eager to learn from and contribute to the research community and the industry, and to advance the state-of-the-art in FL, O-RAN, and data science.