Senior Decision Scientist

Role: Senior Decision Scientist (Lending)Location: Central Birmingham - Office BasedSalary: Up to £80,000 - Depending on experienceAbout LoveyLovey is a fast-growing fintech helping UK businesses access the funding they need to grow. Since 2016, we’ve supported thousands of companies through smarter, faster, and more transparent lending.We’re proud to be a Top 15 fastest-growing finance company, a Great Place to Work, and to hold a 4.9 Trustpilot rating, driven by our focus on innovation, trust, and real customer impact.The RoleWe’re looking for a Senior Decision Scientist to lead the development of cutting-edge credit decisioning models across SME lending.You’ll own the end-to-end model lifecycle, from problem framing through to deployment and monitoring, while working at the intersection of data, risk, and product to shape the future of our lending strategy.What You’ll Do as Senior Decision ScientistBuild and deploy ML and statistical models for credit risk, affordability, and

pricingOwn the full model lifecycle (data, features, modelling, validation, deployment, monitoring)Develop monitoring frameworks and performance dashboardsDrive innovation through new data sources, challenger models, and experimentation (A/B testing)Translate complex models into clear, actionable business insightsRequirements:Strong experience in machine learning within lending (SME essential)Proficiency in Python & SQLProven end-to-end model development experienceBackground in fintech and automated decisioning environmentsSolid understanding of UK credit risk & regulationAbility to communicate effectively with both technical and business stakeholdersConsumer lending experienceExperience with model governance & monitoring frameworksStrong commercial mindset and ownership attitudeWhy Join Lovey?Be part of a high-growth fintech shaping the future of SME lendingWork on high-impact models used in real underwriting decisionsCollaborate with a talented, cross-functional teamJoin a company that truly values innovation, trust, and people #J-18808-Ljbffr