Head of Data Science & Credit Risk – Leadership role at the intersection of machine learning, credit risk, and financial inclusion. Define and scale core decisioning systems powering lending across multiple Southeast Asian markets. Own end-to-end credit intelligence strategy from model development and deployment to portfolio performance and business outcomes.
Accountabilities:
- Define and lead end-to-end data science and credit risk strategy, including underwriting models, portfolio risk frameworks, and decisioning systems
- Design and deploy advanced machine learning models for credit scoring, fraud detection, segmentation, and customer value optimization
- Build real-time and near-real-time decisioning pipelines supporting scalable credit underwriting across multiple markets
- Develop and continuously improve credit risk policies, approval strategies, and risk thresholds aligned with business growth and portfolio health
- Establish MLOps standards for model deployment, monitoring, versioning, and performance tracking in production environments
- Lead portfolio risk analytics, including stress testing, expected credit loss modeling, and early warning systems
- Partner with finance, product, and operations teams to optimize unit economics and capital allocation
- Translate complex analytical outputs into clear, actionable insights for executive leadership and board-level discussions
- Drive experimentation culture, including A/B testing frameworks and data-driven product optimization
- Build and scale partnerships with external data providers, credit bureaus, and alternative data ecosystems
- Recruit, mentor, and develop a high-performing team of data scientists and risk analysts