Job Description

Overview

Key Responsibilities (including but not limited to):

  • Own the end-to-end modelling lifecycle: problem framing, data build, feature engineering, model development, validation, documentation
  • Build and maintain risk and price models using GLMs and machine learning
  • Translate models into implementable rating structures
  • Strong governance: change control, champion–challenger/shadow runs, rollback plans, and clear approvals and audit trails

    • Experience required:

  • Strong general insurance pricing toolkit: GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; experience with tree-based ML (GBM/XGBoost/CatBoost) and regularisation
  • Proficient in R and Python, with strong SQL; comfortable in Git-based workflows and “in the engine room” with proprietary rating systems
  • Hands-on experience taking models from concept to live in rating engines; robust validation, change control and post-l...

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