Group Manager Data Sciences

OverviewWe are seeking an experienced London Market Data Scientist to support the delivery of our tiering enhancement project. The role focuses on applying advanced machine learning techniques to classify risks across all London Market lines of business into low medium and high contractor will enhance existing models using external and internal data build robust Python pipelines and produce explainable outputs that underwriters can trust and ResponsibilitiesEnhance train validate and optimise tiering models for London Market insurance classes using machine learning techniques such as XG BoostEnhance the end-to-end Tiering workflow process: feature engineering data preparation model selection quality assurance and validationImplement scalable reproducible modelling pipelines in PythonProduce clear intuitive model explanations narratives and visuals to underwriters and senior stakeholders for buy-inAddress any concerns around interpretability bias and anomalies in resultsPlay a critical role in the technical rollout of tiering models across all London Market linesDeliver against tight timelines with strong prioritisation and structured executionCollaborate with data science pricing and underwriting colleaguesEnsure high quality reproducible and well-documented code. Required Skills & ExperienceStrong proficiency in Python (pandas scikit learn numpy xgboost SHAP or similar)Proven experience building and understanding machine learning classification models in the London Market insurance context Strong understanding of London Market pricing risk drivers and line-of-business nuances Familiarity with sparse and volatile London Market data Proven ability to influence underwriters and gain buy-in for model adoptionExcellent communication skills able to translate technical details into commercially meaningful insightsTrack record of delivering high-quality work under tight deadlinesCommercially minded able to balance analytical rigour with practical business needsStrong analytical and problem-solving skills with the ability to challenge assumptions constructively and identify issues Experience in building validation checks and controls Self-sufficient proactive and able to drive tasks independently

Qualifications :

Graduate

Remote Work :

No

Employment Type :

Full-time