Senior Credit Risk Data Scientist (m/f/d)

ABOUT US Pliant is a European fintech specializing in B2B payment solutions. Our modular, API-first platform helps businesses streamline spending, improve cash flow, and integrate payments into their financial workflows. Designed for industries with complex payment needs, such as travel and fleet, Pliant enables greater efficiency, control, and profitability. We serve two primary customer segments: - Companies looking to optimize operational processes through intuitive apps and APIs, gaining control, automation, and financial flexibility through extended credit lines. - Businesses such as financial software platforms, ERP providers, and banks that want to launch or enhance their credit card offerings using Pliant’s embedded finance and white-label solutions. Founded in 2020 and headquartered in Berlin, Pliant supports over 4,000 businesses and more than 20 partners globally. As a licensed e-money institution (EMI), we issue credit cards in 11 currencies across more than 30 countries, helping companies streamline and simplify payments. Learn more at http://www.getpliant.com/www.getpliant.com http://www.getpliant.com ABOUT THE ROLE As Senior Credit Risk Data Scientist, you will own the design, development, and deployment of data-driven credit models and automated decisioning systems for small and medium sized enterprises. This is a hands-on technical role that sits at the intersection of data science, ML engineering, and credit risk strategy. You will write production ready code, build end-to-end pipelines, and translate model outputs into real credit decisions. You build things that go live. You own what you deploy. You continuously improve the models, pipelines, and decisioning logic that determine how Pliant extends credit across Europe and the US. You bring both the technical depth to build robust ML infrastructure and the credit intuition to know what good decisioning looks like. If that is you, then join us and work closely with the Head of Risk Strategy and VP of Credit. This position sits directly in the functional domain with exposure to business and full ownership over the outputs you deliver. This is a hybrid role based in Berlin or London, with potential remote flexibility within the EU/UK depending on team and business requirements. WHAT YOU'LL DO - Model development & deployment: Build, validate, and deploy credit risk models owning the full lifecycle from feature engineering and target variable definition through to production deployment, monitoring, and recalibration. - Data engineering: Design and build end-to-end data pipelines in Python and SQL, integrating internal behavioural data, open banking feeds, bureau data, and third-party sources into scalable, production ready workflows using orchestration tools such as Airflow and dbt. - Decision engine ownership: Develop, test, and iterate on automated credit decisioning logic translating model outputs into approval, decline, and limit assignment rules within our decision engine, and monitoring their performance post deployment. - ML infrastructure: Own model deployment, versioning, monitoring, and drift detection. Building the infrastructure that keeps our models performing reliably in production using PSI, Gini, KS, and related diagnostics. - Portfolio analytics: Analyse portfolio performance, identify risk drivers, and translate empirical findings into actionable credit strategy recommendations. - Early warning systems: Design and build EWS frameworks that surface deteriorating credit quality early, enabling proactive portfolio management and collections prioritisation. - Collaboration: Partner with Risk Management, Data, and Engineering teams to build E2E data processes together. Manage cross functional projects and drive delivery. - Communication: Facilitate smooth and fact based information flow between your colleagues. Support data driven decision making within the credit risk domain. Support the development of a culture of open dialogue, focused on mutual