Senior Pricing Analyst
Selby Jennings is proud to be working in partnership with a leading personal lines insurer, currently seeking a Senior Pricing Analyst to join their pricing team.
This is a unique opportunity for a technically skilled and commercially focused analyst to play a central role in delivering the organisation's pricing strategy for the household portfolio. The successful candidate will contribute to the development of sophisticated pricing models and optimisation techniques that directly impact profitability, growth, and strategic decision-making.
You'll work closely with pricing analysts, underwriters, and senior stakeholders, applying advanced statistical and machine learning methods to deliver actionable insights. The role offers exposure to a wide range of modelling approaches, rating engines, and behavioural analytics, with a strong emphasis on innovation, leadership, and continuous improvement.
Key Responsibilities:
- Develop and coach Pricing Analysts, supporting technical growth and capability.
- Build and validate predictive machine learning models to improve pricing accuracy.
- Deliver accurate datasets for modelling, pricing, and performance monitoring.
- Perform price optimisation and enhance existing processes using innovative techniques.
- Deploy and review rates in live rating engines.
- Maintain behavioural models incorporating machine learning algorithms.
- Combine modelling results, MI, and strategic targets to assess pricing performance.
- Coordinate pricing decisions and implementation across teams and governance bodies.
- Lead and manage projects across the full pricing control cycle.
- Influence senior management and stakeholders across Pricing and Underwriting.
- Act as deputy for senior colleagues when required.
Role Requirements:
- Degree (or equivalent) in a numerical discipline.
- 3+ years of experience in insurance pricing or a related analytical field.
- Proficient in SAS and at least one of R, Python, Matlab, or Octave.
- Experience with modelling techniques such as GLMs, GBMs, GAMs, Decision Trees, Random Forests, SVMs, and Neural Nets.
- Strong understanding of price optimisation methodologies.
- Proven ability to communicate complex statistical concepts to non-technical audiences.
- Strong stakeholder engagement and influencing skills.
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