Faculty profile: Dr. Samuel Osei

Dr. Samuel Osei, a lecturer in applied analytics, specializes in machine learning and volatility forecasting. He brings industry consulting experience and a teaching style that prioritizes technical transparency and open critique.

Dr. Samuel Osei is known for his applied research in machine learning and volatility forecasting, focusing on market data modelling and real-world analytics challenges. He has published technical articles on the integration of alternative datasets and the critical evaluation of model outputs in financial contexts. His work emphasizes the practical implications of predictive analytics, especially where market conditions deviate from theoretical expectations.

Dr. Osei’s industry consulting spans banking and asset management, where he advises analytics teams on robust model development, scenario testing, and technical documentation. His expertise is frequently sought for data-driven audit processes and the design of transparent modelling frameworks.