Head of Data Science & Credit Risk (Remote)

About the role

We’re seeking a Head of Data Science & Credit Risk to lead our ML‑driven underwriting strategy and strengthen risk decisioning across Southeast Asia. In this role you’ll combine deep data science expertise with credit risk leadership, owning the full lifecycle from model development to business impact.

Key responsibilities

• Design, test, and deploy ML models for credit decisioning, fraud detection, and risk segmentation, ensuring they are interpretable, fair, and robust.
• Develop underwriting algorithms that leverage alternative data to improve risk assessment and expand financial access.
• Establish MLOps practices for model versioning, experimentation, deployment, and ongoing monitoring across multiple markets.
• Define and manage credit risk frameworks, policies, and approval strategies tailored to each market, monitoring key risk metrics and early‑warning signals.
• Build, lead, and mentor a team of data scientists and risk analysts while remaining hands‑on with technical work.

Required profile

• At least 10 years of combined 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 and managing credit policies and portfolios at scale across multiple products or markets.
• Strong statistical and mathematical expertise, with hands‑on experience in experimentation and A/B testing.
• Excellent communication skills to explain complex models and credit risk concepts to business stakeholders.

Required skills

• SQL
• GCP BigQuery (or comparable cloud data platforms)
• MLflow or similar frameworks for production model development and deployment

What we offer

• A competitive salary based on experience and location.
• Equity participation.
• Opportunities to learn, grow, and shape a growing data science and credit risk function.
• The chance to help redefine financial services for underbanked employees.