ML engineer

Purpose of the role

Build, train, deploy, and maintain all analytical and machine learning models serving the Investment Division and, in later phases, the Group’s operating divisions. This includes the five core investment model families (factor decomposition, anomaly detection, NLP/document intelligence, portfolio optimisation, manager screening) and operating division models (DuPont automation, credit scoring, demand forecasting). Work directly with portfolio analysts to validate model outputs and iterate based on domain feedback.

Key responsibilities

• Build and deploy factor exposure decomposition models: rolling Fama-French, Barra, and custom factor regressions for equity and fixed income portfolios. Daily batch processing on gold layer return series.
• Build and deploy anomaly detection for manager monitoring: style drift detection (rolling z-scores on factor loadings), return pattern breaks (CUSUM...