Head of Data Science

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.

• Credit risk modelling experience in UK lending - Significant experience in credit risk assessment within UK consumer lending, ideally motor finance, point-of-sale or a fast-growth fintech.
• Hands-on data science - You've personally built risk models and put them into production, not just specified them. You're expert in Python and SQL, with a strong grounding in machine learning.
• Product and delivery mindset - You think like a product manager as much as a data scientist. You define the problem, prioritise ruthlessly, bring Product, Engineering, Credit, Ops and Collections along with you, and deliver outcomes, not just models.
• Agentic AI know-how - Practical experience building with LLMs and AI agents on real decisions, not just demos, including evaluation, guardrails and governance.
• Production engineering discipline - You're at home with Git, testing, CI/CD, cloud platforms and model monitoring, and you ship code you'd trust with live lending decisions.
• Commercial and clear-headed - You know friction has a cost, you design controls proportionate to the risk, and you can explain it equally well to engineers and the board.
• Genuine excitement for Carmoola's mission and the chance to shape the future of how people get on the road.