Overview
Key Responsibilities (including but not limited to):
Own the end-to-end modelling lifecycle: problem framing, data build, feature engineering, model development, validation, documentationBuild and maintain risk and price models using GLMs and machine learningTranslate models into implementable rating structuresStrong governance: change control, champion–challenger/shadow runs, rollback plans, and clear approvals and audit trailsExperience required:
Strong general insurance pricing toolkit: GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; experience with tree-based ML (GBM/XGBoost/CatBoost) and regularisationProficient in R and Python, with strong SQL; comfortable in Git-based workflows and “in the engine room” with proprietary rating systemsHands-on experience taking models from concept to live in rating engines; robust validation, change control and post-l...