About this role

Leading the development of analytical solutions and models to support underwriting and pricing decisions.
Designing, building and maintaining robust data pipelines, datasets and codebases that support regular MI, dashboards and advanced analytics.
Taking ownership of more complex reporting and forecasting processes, ensuring they are accurate, scalable and well-documented.
Enhancing existing MI for Underwriting and Performance KPIs, introducing more advanced analytics.
Developing and maintaining financial and performance forecasting models to support planning and portfolio steering.

Bachelor’s degree (or equivalent) in Mathematics, Statistics, Actuarial Science, Data Science, Computer Science, Engineering, Economics, Finance or a related quantitative discipline.
Typically 2–5 years of experience in data science, advanced analytics, actuarial, or a closely related field.
Strong coding skills in at least one of Python or R.
Practical experience with statistical modelling and/or machine learning techniques, such as: Generalised linear models (GLMs) or other regression methods, Tree-based methods (e.g. random forests, gradient boosting), Time series modelling and forecasting, Clustering and segmentation technique
Experience with data visualisation tools such as Power BI or Tableau.

Data Scientist – Underwriting Analytics

Key skills