At BPI Asset Management, I built quantitative risk models and automated analytics and Power BI reporting for portfolio monitoring across €6.6B AUM. I automated daily KPI reporting in Python and R, improving portfolio analysis efficiency by 400%, and developed and back-tested VaR, Expected Shortfall, and factor models.
I also developed a TCFD/ESG evaluation pipeline integrating MSCI data into dynamic reports. My work draws on financial mathematics, portfolio risk, stress testing, and statistical modelling, including a project migrating a predictive machine-learning factor model from SPSS to Python.

