Femi is a data analyst and clinical epidemiologist with MSc degrees in health data science and clinical epidemiology. His background combines clinical and analytical experience, giving him a unique perspective on how data can improve healthcare delivery and outcomes. He works with large and complex datasets — often from electronic health records and public health sources—using tools like SQL, Python, R, and Power BI to uncover insights, build predictive models, and support evidence-based decisions.
Throughout Femi’s career he has worked closely with clinicians, researchers, and decision-makers, translating data into meaningful solutions that align with real-world healthcare challenges. He is passionate about improving health systems through responsible data use, equity-focused analysis, and continuous learning. Whether it’s developing tools for better service planning or diving into research to support innovation, he enjoys projects that have a direct and positive impact on patient care and population health.
