As the Director of Decision Science, you will play a pivotal role in shaping the modelling strategy for a rapidly growing embedded finance provider. This position offers the opportunity to take full ownership of the underwriting and acquisition modelling roadmap, lead two technical teams, and influence the deployment of advanced models to boost customer growth across multiple international markets. The client operates across the UK, Europe, and North America, using partner-supplied data and advanced modelling techniques to deliver personalized financial products to small and medium-sized businesses.
In this role, you will oversee the development, validation, and monitoring of underwriting and acquisition models across various regions. You will be responsible for setting modelling standards and defining best practices for build quality, documentation, and governance. Additionally, you will guide the long-term roadmap for how models support customer acquisition, pricing, and portfolio performance. An important aspect of this position involves integrating MLOps and model deployment into the decision science function. Collaboration is key, as you will partner with product, engineering, and commercial teams to translate model outputs into meaningful business decisions. Furthermore, you will manage the model development and acquisition analytics teams, ensuring technical excellence and providing clear development pathways.
The ideal candidate will have strong experience in building predictive models in Python, using techniques like gradient boosting, as well as experience in consumer or commercial risk modelling and decision science environments. A commercially minded approach to acquisition, pricing, and performance is essential. You should be confident in managing the full model lifecycle, including design, testing, deployment, and monitoring, and possess effective leadership and stakeholder management skills across technical and non-technical domains. While experience with MLOps or R is beneficial, it is not required.