> Markdown version of [/jobs/ext/3325412-data-scientist-credit-risk-modelling](https://www.wearedevelopers.com/jobs/ext/3325412-data-scientist-credit-risk-modelling). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Credit Risk Modelling - **Company:** iwoca - **Location:** London, UK - **Experience:** Expert - **Salary:** £90,000.0 - £120,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Artificial Neural Networks, Iterative and Incremental Development, Python (Programming Language), Machine Learning, Large Language Models, Xgboost - **Published:** September 5, 2026 - **Apply:** https://startup.jobs/senior-data-scientist-credit-risk-modelling-iwoca-co-uk-9923431 ## About the Role Essential: * Communication. You write and speak clearly, directly, and concisely. You adapt technical detail to your audience. * Statistical foundations. You have a background in probability and statistics from a quantitative field. You reason about uncertainty and calibration as first-order concerns. * Production ML. You have built and shipped supervised ML models end to end - exploration, training, deployment, monitoring. * Research mindset. You proactively explore new ways to add value. R&D time is when you expect to find the next step change. * Judgement. You critically evaluate model output - yours, a colleague's, or an LLM's - and can explain why a choice is right. You defend your reasoning under challenge, and challenge others' when the evidence points elsewhere. You've influenced technical direction beyond your own projects. * Project leadership. You've owned modelling projects end to end, from spotting the opportunity through framing, method choice, shipping, and landing the commercial impact. You move fast, iterate, and update on new evidence rather than chase perfection. * AI fluency. You use AI as a primary tool. You prototype with it, automate with it, and take on R&D that would not otherwise be viable. You use judgement on where it helps and where it doesn't. Bonus: * Domain experience. You have worked in credit risk, lending, or customer lifetime value modelling. * Non-linear methods. You have shipped gradient boosting or neural networks on tabular data in production. * Bayesian methods. You have used hierarchical models, MCMC, or Bayesian updating in real work. * Time series modelling. You have modelled temporal data where autocorrelation, drift, or seasonality mattered. * Python. The stack the team uses. ## Description You'll shape how iwoca models credit risk - setting the technical direction on multi-quarter projects, and lifting the bar for the team as you go., You'll own credit and CLtV modelling projects end to end, from spotting where the modelling stack is holding the business back through to landing the change. The work spans keeping production models healthy, incremental development, and research that reshapes how the models work. AI has lowered the cost of prototyping enough that ideas which used to sit below the priority line are now viable, so the R&D share of the role is growing., * Causal estimation of offer terms. Modelling how amount, duration, and price shape customer outcomes. * Unifying auto and manual models. The two families were built without forced technical alignment. Finding a principled way to unify them on a common cost function is open work. * IFRS accounting model. A multi-stage credit model where information propagates back from later-stage recovery predictions to sharpen upfront loss estimates. * Generalising credit and CLtV. 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