FINN

• Build and ship backend services that power our financial products — APIs, automation pipelines, and cloud infrastructure • Own features end-to-end: dig into the problem, design the approach, ship fast, and iterate based on real usage • Contribute to technical direction — advocate for better patterns, tooling, and developer experience • Partner with product and engineering to define solutions, not just execute specs • Write clean, reliable code at a high pace — quality and speed, not one or the other • Raise the bar for the team through code reviews, technical input, and leading by example

• Design and implement advanced ML models for credit decisioning, fraud detection, and risk segmentation • Lead development of next-generation underwriting algorithms using alternative data sources • Build and deploy real-time scoring models that scale across multiple markets • Champion model interpretability and fairness in AI-driven credit decisions • Drive machine learning adoption across the organization - eg. experimentation on customer-value and monetization models, marketing attribution solutions. • Establish MLOps best practices for model versioning, monitoring, and deployment • Develop comprehensive credit risk frameworks adapted to each market's unique dynamics • Design approval strategies and risk thresholds that optimize for growth and portfolio health • Create early warning systems for portfolio deterioration using predictive analytics • Lead stress testing and expected credit loss modeling initiatives • Partner with Finance on provisioning and capital allocation strategies • Build and mentor a high-performing team of data scientists and risk analysts • Drive data science roadmap aligned with business expansion goals • Present risk insights and recommendations to executive team and board • Establish partnerships with alternative data providers and credit bureaus • Foster a culture of experimentation and data-driven decision making • Optimize approval rates while maintaining target default rates • Reduce time-to-decision through model automation • Identify new customer segments and product opportunities through advanced analytics • Support market expansion with localized risk models and regulatory compliance • Drive unit economics improvement through sophisticated segmentation

• Monitor key risk metrics (e.g., default rates, approval rates) and investigate significant changes. • Analyze large datasets to identify trends, anomalies, and areas for improvement in risk management processes. • Simulate the impact of credit policy or model changes, support A/B tests, and help guide rollouts to improve approval funnel performance. • Track performance post-implementation and refine strategies using feedback loops and business KPIs. • Develop, test, and deploy risk models in an iterative, agile manner. • Monitor the performance of risk models, tracking feature stability, accuracy, and drift over time. • Understand country-specific factors such as onboarding processes, customer limit management, and local alternative data sources. • Collaborate with internal and external data vendors to evaluate and integrate new data sources. • Contribute to the setup of early warning signals for portfolio deterioration, using a mix of quantitative and qualitative data.

• Build and ship complex, user-facing features across web and mobile (Angular + Ionic) • Own features end-to-end: dig into the problem, design the approach, ship fast, and iterate based on real usage • Contribute to technical direction — advocate for better patterns, tooling, and developer experience • Partner with product and design to define solutions, not just execute specs • Write clean, performant code at a high pace — quality and speed, not one or the other • Raise the bar for the team through code reviews, technical input, and leading by example