Focus on:

• Growth: pricing & aggregator ranking optimization
• Risk: building and implementing open banking risk models; feature generation
• Product: backend engineering of Credit Decision Engine
• Automation: analysis & implementation of automation procedures
• Infrastructure: AWS, Docker & database integration for Data Science project enablement

Delivered a range of internal Data Science projects:

• Extracted risk insights from Environment Agency Flood API, utilizing Spatial Statistics methodologies. XGBoost frequency model tuned via Bayesian Optimization supplemented current pricing structure, identifying Loss & Combined Ratio patterns.
• Manual rate changes to current pricing structure, often for high-dimensional tables, to identify tactical pricing strategies, gaining an edge over competitors in subsets of the market.
• Modelling of Price Elasticity. Project involved significant exploratory analysis and an automated RMarkdown report using ggplot.
• Creation of Storm Peril rate structure for more accurate pricing of peril-specific risk. Spike-Slab prior for identification of potentially useful features. GLM built iteratively using Lift and consideration of MultiCollinearity and domain knowledge to ensure logical rates.
• Technical Pricing Analysis including derivation and implementation of rate index for neutralization following FCA regulatory changes.