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- Designing and developing innovative pricing models
- Conducting price optimisation and customer lifetime value modelling
- Extracting insights from data using tools such as SAS, SQL, Python, and R
- Building and maintaining predictive models using a range of statistical techniques
- Collaborating with underwriting, data science, and other business units
- Presenting actionable insights to senior stakeholders to drive commercial decisions
- Leading continuous improvements in process and model performance
- Experience in general insurance pricing (personal lines preferred)
- Hands-on knowledge of tools such as SAS, SQL, Python, R, (Emblem OR Radar)
- Strong understanding of predictive modelling techniques (e.g. Logistic Regression, GBMs, Decision Trees, Clustering)
- A quantitative degree in Mathematics, Statistics, Actuarial Science, Engineering, or similar
- Excellent communication skills with the ability to translate complex findings into business actions
- Curiosity and drive to challenge the status quo
- A logical mindset and a self-starter attitude
- Passion for innovation and improvement
- A collaborative team player with a sense of humour
