Data Scientist - Credit Cards

Data Scientist - Credit Cards Hybrid in London, United Kingdom We're looking for a Data Scientist to join the Credit Cards team. You'll build the credit risk, pricing, and customer lifetime value models behind iwoca's business credit card – who gets a card, with what features, and at what rate.   The company Small businesses move fast. Opportunities often don't wait, and cash flow pressures can appear overnight. To keep going, and growing, SMEs need finance that's as flexible and responsive as they are. That's why we built iwoca. Our smart technology, data science and five-star customer service ensures business owners can act with the speed, confidence and control they need, exactly when it's needed. We've already cleared the way for 100,000 businesses with more than £4 billion in funding. Our passionate team is driven to help even more SMEs succeed, through access to better finance and other services that make running a business easier. Our ultimate mission is to support one million SMEs in their defining moments, creating lasting impact for the communities and economies they drive. The team iwoca launched its business credit card at the start of 2026. It gives small businesses a fast, flexible way to pay for what they need and control their cash flow, alongside iwoca's loans. The card is a core part of iwoca's long-term growth. The Credit Cards team builds the card on iwoca's existing lending infrastructure and customer base. The team is made up of commercial strategy product, engineering, operations, and a data scientists. The role As a Data Scientist in Credit Cards, you'll do the analysis and modelling for the card's commercial decisions. You'll often have small samples and incomplete data, which suits Bayesian methods. You'll quantify the uncertainty in each estimate and explain what it means for the decision. You'll run your own projects, from framing the question with the commercial lead to helping the team act on the result. Your models will shape how the card grows. You will be embedded in a broader Credit Cards Team and learn about the product and customer needs. You'll share methods with Credit Risk Modelling, especially where card and lending models overlap, and with data scientists across iwoca in the analytics guild. Live project examples: • Credit limits. Setting initial limits that balance risk with what each customer needs, and designing a framework that adjusts them as spending and repayment data comes in. • Pricing. Modelling how interest and fees affect take-up and spending,, to find pricing that works for iwoca and its customers. • Customer lifetime value. Estimating activation, spending, and retention from early signals, and updating the estimates as each cohort matures. • Card and loan together. Measuring cross-sell and combined credit exposure for businesses that hold both the card and an iwoca loan. Designing the mechanisms to optimise how the two products interact. The requirements Essential: • Statistical foundations. You have a background in probability and statistics from a quantitative field. You reason about uncertainty and calibration as first-order concerns. • Bayesian reasoning. You've used priors, updating, and hierarchical models in real work. You know when a Bayesian model is worth the extra complexity, and when something simpler will do. • Analytical ownership. You've taken loosely defined problems from framing the question to a decision the business acted on. • Business curiosity. You've used what you learnt about a business's customers and economics to shape your analysis. • AI leverage. You've used AI to produce work you couldn't have delivered without it – a prototype, an automation, or a modelling pipeline others use. You judge where it helps and where it doesn't, and you che