Jonathan's interest in the mathematical sciences began with a bachelor’s degree in theoretical and computational physics. He continued his studies with a master’s degree in biomedical research at Imperial College London, where he specialized in the mathematical modeling of infectious diseases. After completing his master’s degree, he made the move into research and then into corporate training, where he’s been supporting data professionals transform their skills for over half a decade.

Over the course of his career Jonathan has worked on many challenging data science projects. One of his first roles after completing his postgraduate degree was as a mathematical modeler working with an international team of researchers looking into the healthcare system of sub-Saharan African countries. Leveraging his expertise in machine learning he worked to successfully reconcile incongruous medical supply chain data sources to quantify stock shortages in the region. As a keen problem-solver, he likes discovering how Data Science and AI can be applied to real-world data.

The area of his work that he is most passionate about is education. Jonathan first began teaching during his master’s degree, where he provided personalized tutorial sessions reviewing the Python code of medical students completing their computational medicine module. He later became an early hire to a data apprenticeship start-up, where he trained data professionals in a range of industries including retail, healthcare, and finance. During his career, he has particularly enjoyed the challenge of translating complex topics, like the latest in machine learning models, into engaging applied sessions for data professionals.

Jonathan is always adding to his knowledge of the fast-moving fields of Data Science and AI to ensure that he is up to date with the latest developments. Ensuring he can provide informed expert training to individuals looking to build lasting, performant, and reliable solutions.