You'll take the reins on building and owning Carmoola's data science strategy – from designing and deploying the AI to assess risk across our application flow, to using Open Banking to provide frictionless, accurate affordability assessments. You'll have a huge amount of autonomy and responsibility from day one, and the opportunity to define what AI-native risk and affordability at Carmoola really means.
This is a high-impact role for someone who is as comfortable writing and shipping production code as presenting to leadership, thinks commercially about the cost of friction, and knows how to build something from scratch. You won't hand requirements to another team – you'll set the strategy, build the models and agents yourself, deploy them into live decisioning and prove their impact on real losses.
Own our risk prediction strategy - Set the direction across data science methods, data sources and platforms. Decide what we build versus buy, and balance loss prevention against friction for customers and dealers.
Lead delivery across the business - Own the data science roadmap. Shape requirements with Product and Engineering, work with Credit, Ops and Collections to make models fit how the business really runs, and keep delivery moving from idea to live impact.
Develop the models underneath - Build Gradient Boosting Machines to predict risk, Open Banking categorisation models, plus look for other uses of data science techniques to meet our goals.
Ship it to production - Own deployment end to end, from tested, version-controlled code and CI/CD to safe releases and live monitoring for drift and performance, with clear governance and human oversight wherever customers are affected.
Turn data into decisions - Deliver analytics and MI that show how your models are winning, and report against risk appetite to senior leadership and the board.
