Data Scientist

What’s Yonder? “It's as if Time Out, Amex and Monzo had a baby” - Will T, Yonder Member Yonder is a credit or debit rewards card that is designed to be fair, flexible, and actually enjoyable to use. No confusing terms. No dusty points system. Just rewards that actually feel rewarding - from bao to beers to a boarding pass. If you want to work somewhere that's at a genuine inflection point, and on a product that our members really love, come Yonder with us. Sounds cool. What’s my part in this? We’re looking for a Senior Data Scientist to build the predictive models that sit behind some of Yonder’s most important decisions. You’ll work across credit acquisition, portfolio management, collections, fraud and rewards, using our data to improve how we select customers, manage risk, allocate credit, intervene when things go wrong and personalise the Yonder experience. This is a senior, hands-on individual contributor role reporting directly to the CRO, who owns Risk and Analytics at Yonder. You won’t be sitting in a central data science team waiting for problems to arrive. You’ll work directly with the people making the decisions, understand the commercial problem, build the model and help turn it into something that actually runs in production. That means everything from feature engineering and model development through to validation, implementation, monitoring and explaining what the model is telling us. We care far more about models that improve decisions than models that are technically interesting but never make it into the product. Yonder moves quickly. We have a growing customer base, increasingly rich behavioural data and a lot of decisions that can be made materially better through predictive modelling. We’re looking for someone excited by the opportunity to build that capability rather than inherit a finished machine learning stack. What you’ll do Building our acquisition models. You’ll develop and continuously improve models that help us understand applicant risk, affordability and expected customer value. You’ll use bureau, application and alternative data sources to make better onboarding decisions. Building behavioural models for portfolio management. You’ll predict how existing members are likely to behave to help our credit strategy team to use those predictions to improve credit profitability. Improving collections strategy through prediction. You’ll build models that help us identify how members will respond to different interventions and allow our Collections team to focus their efforts where it has the greatest impact. Building better fraud models. You’ll work with our Fraud and Financial Crime team to identify suspicious behaviour earlier, improve fraud detection and reduce unnecessary friction for genuine members. Using machine learning to improve rewards. You’ll work closely with our AI engineers to leverage member data to help surface the right reward at the right time. Owning the modelling lifecycle.…