Head of Data Science & Credit Risk

About the role

We are looking for a senior leader to own the end‑to‑end machine‑learning driven underwriting strategy and credit‑risk decisioning across Southeast Asia. The role combines deep data‑science expertise with credit‑risk leadership, overseeing model development, deployment and business impact while building a high‑performing team.

Key responsibilities

• Design, test and deploy ML models for credit decisioning, fraud detection and risk segmentation, ensuring they are interpretable, fair and robust.
• Develop and manage credit‑risk frameworks, set risk thresholds, monitor key risk metrics and lead stress‑testing and expected credit loss modelling.
• Build, lead and mentor a team of data scientists and risk analysts, while remaining hands‑on with technical work.
• Establish MLOps practices for model versioning, experimentation, deployment and ongoing monitoring across multiple markets.
• Communicate model performance, portfolio trends and strategic recommendations to the executive team and board.

Required profile

• At least 10 years of experience in data science, machine learning and consumer credit risk within fintech or digital lending.
• Proven track record of building, deploying and monitoring production ML models in real‑time decision pipelines.
• Experience developing credit policies and managing portfolios at scale across multiple products or markets.
• Strong statistical and mathematical background with hands‑on experience in experimentation and A/B testing.
• Excellent communication skills and ability to translate technical decisions into business outcomes.

Required skills

• SQL
• GCP BigQuery (or other cloud data platforms)
• MLflow or similar model‑deployment frameworks
• Machine learning and statistical analysis

What we offer

• Competitive salary based on experience and location.
• Equity participation.
• Opportunities to shape a growing data‑science and credit‑risk function.
• Chance to help redefine financial services for underbanked employees.