Small businesses drive the economy. They build, hire, innovate, and take risks. But when they need financing, things still move at the speed of paper. Endless forms. Long approvals. Decisions that rely more on history than on logic. We built BridgeFund to fix that. What takes weeks elsewhere happens here in seconds - a small business applies in 3 minutes, and our model decides in one. No paperwork. No waiting. No human bottlenecks. Just smart tech making fair decisions, fast. That’s how we grew 74% last year, provided over €500 million in funding, and will close 2025 profitably.
“BridgeFund is a fantastic place to work because it doesn't feel like work. It's not the catered lunch, company boat or other great benefits (although those perks don't hurt!). It's the people, the purpose and the passion we bring to work every day.”
We’ve built a platform that turns business financing from a slow, manual process into a one-second decision. Now we’re looking for someone to make it even smarter. As a Data Scientist at BridgeFund, you’ll help shape the logic that decides how millions in business funding flow through our system. You’ll work end-to-end: designing, training, and deploying models that predict risk, assess creditworthiness, and guide portfolio performance. You’ll turn raw data into clear, actionable insight: the kind that changes how we lend, price, and grow. You’ll be part of a compact, high-impact team of data scientists, engineers, and analysts who prefer building over talking. We test fast, ship often, and only celebrate what works in production. We’re far from done, and that’s exactly how we like it.
Build and own predictive risk models (PD, churn, stress testing)
Analyze drivers of risk and performance and translate insights into improvements
Design and validate features that make models more robust and explainable
Work with engineers to bring models into production and keep them running smoothly
Translate insights into clear, data-driven decisions for stakeholders
Stay sharp on trends, regulations and new modelling techniques
As a senior you will, coach junior team members and help the team grow
Senior experience as a Data Scientist or Credit Risk Modeller in a bank, fintech or lending company.
Proven experience building and owning credit risk models (e.g. PD, LGD, loan capacity, portfolio models).
Strong skills in Python and SQL.
Experience taking models from data to production and embedding them in real credit decisions (acceptance, pricing, credit limits).
Strong understanding of lending portfolios and the growth vs risk trade-off, with experience contributing to risk appetite & portfolio steering.
Comfortable working with engineers, analysts and risk stakeholders in a cross-functional environment.
Business-driven: able to link models and analyses to approval rate, losses, margin and portfolio performance.
Structured, proactive and able to take ownership in a fast-growing scale-up environment.