Data Scientist - iwocaPay Risk Squad

iwoca·Londonmid

In short

→Científico de datos que construye modelos de crédito automatizados para pymes en un producto B2B Buy Now Pay Later.
→Trabajas en equipo pequeño, desde el diseño hasta el monitoreo, con impacto comercial directo en decisiones de financiación.
→Tienes autonomía total sobre tu modelo y gran influencia en cómo se desarrolla la arquitectura de riesgo.

Clear communication – you can adapt technical detail for non-technical colleagues working

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What they ask for

✓Experiencia end-to-end en modelado supervisado con datos tabulares en producción.
✓Fundamentos sólidos en estadística, incertidumbre y calibración de modelos.
✓Capacidad para trabajar de forma autónoma en entornos inciertos y no estructurados.
✓Habilidades de ingeniería de datos para construir pipelines y gestionar conjuntos de datos.
✓Fluidez en IA para acelerar trabajo analítico y de ingeniería.
✓Capacidad de comunicación clara con personas no técnicas en producto, riesgo y liderazgo.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonSupervised machine learningTabular dataTime series dataModel calibrationUncertainty quantificationAIData engineeringGradient boostingNeural networks on tabular dat

Who should you write to at iwoca?

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Hybrid in London, United Kingdom We're looking for a Data Scientist to join the iwocaPay Risk Squad You'll own credit models that decide who iwocaPay can safely fund and on what terms. The team is small, the product is growing, and you'll shape how risk modelling is built – not just maintain what exists. 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 function iwoca's Data Scientists specialise in supervised machine learning, statistical inference and exploratory data analysis, focusing on tabular and time series data. Our work emphasises quantitative predictions through the analysis of conditional probabilities and expectations, using medium-sized datasets. The team iwocaPay is iwoca's B2B Buy Now Pay Later product. The Risk Squad owns the automated credit decisioning and fraud prevention models that influence every lending decision the product makes. The squad also handles counterparty risk, portfolio-level strategy, and ongoing monitoring of losses, chargebacks, and segment performance. The role You'll co-own the full credit modelling stack with one other data scientist. You’ll collaborate on model design, review each other's work, and choose what to prioritise. Your models directly control which small businesses get access to funding, on what terms, and how far the product can grow. What you'll get out of it: Complex problems to solve Work on interesting, open modelling problems rather than maintenance. Improving how the model performs across segments, test more advanced approaches, and build models from scratch for new products. Real influence You own the models end to end, and your decisions carry commercial weight. Room to develop A small team on a growing product means broad remit, fast growth, and a say in how the team's pipelines, monitoring, and processes get built. The requirements Essential: Expertise in supervised machine learning on tabular data, with experience building and iterating production models end to end (exploration through deployment and monitoring). Strong statistical foundations in probability, uncertainty quantification, model calibration, and in reasoning about where a model is likely to be wrong. Ability to work independently in a messy, early-stage environment – scoping problems, building infrastructure, and shipping models autonomously Pragmatism about what ‘good enough’ looks like commercially, balanced with rigour on high-stakes models. Data engineering capability – building pipelines and managing datasets alongside the modelling work. AI fluency – using AI to build, automate, and accelerate substantive analytical and engineering work. Clear communication – you can adapt technical detail for non-technical colleagues working in product, risk, and leadership. Bonus: Experience with credit risk modelling or financial services lending. Familiarity with transfer learning, domain adaptation, or techniques for combining datasets of different sizes and relevance. Experience with non-linear models (gradient boosting, neural networks on tabular data) in production settings. Python proficiency – it's what the team uses day to day. The salary We expect to pay from £60,000 – £80,000 for this role.

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