Lecturer in Business Analytics
Background
BSc Physics (Chile); Industrial Engineer (Chile); MSc Statistics and OR (Edinburgh); PhD (Edinburgh).
Dr. Victor Medina-Olivares has a multidisciplinary background in physics, industrial engineering, and statistics, with extensive experience spanning academia, research, and consultancy.
His teaching portfolio includes programming in Python, R, and Stan, as well as Bayesian data analysis, applied econometrics, probabilistic machine learning, and causal inference. With teaching experience in Germany, the UK, and Chile, he has taught at both undergraduate and postgraduate levels.
Beyond academia, Dr. Medina-Olivares has worked in both the public and private sectors. As a researcher at the Financial Market Commission (formerly SBIF), he developed predictive risk models for the Chilean financial system, contributing to its resilience and sustainability. In consultancy, he designed and implemented advanced risk models for financial institutions, leading interdisciplinary projects that bridge academic innovation and industry challenges.
Dr. Medina-Olivares focuses on developing statistical methods to address complex, real-world problems, with applications in credit risk assessment, consumer behaviour analysis, climate change, open banking, fintech, and quantitative marketing.
Research Interests
- Probabilistic Machine Learning
- Bayesian Analysis
- Predictive Modelling
- Spatial Statistics
- Causal Inference