Jeffrey is a data professional with strong mathematical foundations, proven communication skills, and extensive experience in data engineering and analytics. His data pipeline and modelling expertise can be seen through his work building automated architectures, developing CDC-enabled pipelines, and delivering end-to-end analytical solutions for clients. His technical capabilities are also reflected on his GitHub profile, which contains numerous SQL and Python projects, and through his applied data engineering and data preparation work across multiple client projects at The Information Lab and beyond. Jeffrey’s spectrum of experiences includes being trained to lead a team at KFC and completing a teaching placement where he addressed mathematical anxiety in the classroom through both theoretical research and practical techniques.
Jeffrey graduated from the University of Cambridge with a Master of Advanced Study in Pure Mathematics. Here, he strengthened his ability to communicate complex technical ideas clearly, restructuring advanced mathematical concepts into accessible language—demonstrated, for example, in his essay “The Hodge Decomposition Theorem.” Jeffrey’s academic background deeply informs his understanding of data systems and enhances his ability to share knowledge effectively, whether through documentation, workshops, or peer support.
Outside of work, Jeffrey is a passionate music producer and instrumentalist with published work. He also enjoys playing chess, cooking, and travelling, always seeking new challenges and new opportunities to learn.