Emmanuel Kalunga is a data science leader with a PhD in Computer Science and Electrical Engineering and over a decade of experience turning complex signals and business data into actionable strategy. He has led and scaled data teams across fintech, telecommunications, and on-demand delivery—currently heading Data Science & Analytics at Sanlam Fintech—bridging machine learning, operations research, and business intelligence to drive operational efficiency and product impact. His research background in EEG-based brain–computer interfaces at Université Paris-Saclay informs a rigorous experimental approach to building reference datasets, reproducible pipelines, and peer-reviewed contributions to the BCI community. Comfortable moving between hands-on modeling and executive data strategy, Emmanuel is known for aligning analytics roadmaps to business outcomes and embedding AI into decision workflows. A less obvious strength is his track record of producing production-ready Python tooling and datasets from academic-grade experiments, enabling both research and commercial deployment.
10 years of coding experience
8 years of employment as a software developer
Master's Degree, Electrical and Electronics Engineering, Master's Degree, Electrical and Electronics Engineering at ESIEE PARIS
Certificate, Project Management, Certificate, Project Management at The George Washington University - School of Business
Doctor of Philosophy (Ph.D.), Computer Science, Automation and Signal Processing, Doctor of Philosophy (Ph.D.), Computer Science, Automation and Signal Processing at Université Paris-Saclay
Doctor of Technology (DTech), Electrical and Electronics Engineering, Doctor of Technology (DTech), Electrical and Electronics Engineering at Tshwane University of Technology
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