Head Of Data Science & Credit Risk

Role overview This senior leadership role directs machine-learning-driven underwriting and credit risk strategy across multiple Southeast Asian markets. The position blends hands-on data science with portfolio-level risk ownership, partnering closely with engineering, product, and finance to expand responsible credit access while protecting portfolio performance.

Responsibilities - Design, test, and deploy production ML models for credit decisioning, fraud detection, and customer risk segmentation. - Build alternative-data underwriting algorithms and real-time scoring pipelines that scale across multiple markets. - Develop credit risk frameworks, policies, and approval strategies tailored to each jurisdiction, including thresholds, segmentation, and early-warning monitoring. - Lead stress testing, expected credit loss modeling, and provisioning analyses in partnership with finance. - Establish MLOps practices for versioning, experimentation, deployment, and ongoing model monitoring, including drift and stability checks. - Manage, mentor, and technically engage a team of data scientists and risk analysts, owning the roadmap and communicating performance to executives and the board.

Requirements - At least 10 years of combined experience in data science, machine learning, and consumer credit risk within fintech, digital lending, BNPL, or earned wage access. - Demonstrated track record building and operating production ML models inside real-time or near-real-time decisioning pipelines. - Experience developing and managing credit policies and portfolios at scale across multiple products or markets. - Strong classical statistics and modern ML expertise, plus fluency in SQL and exploratory data analysis on cloud data platforms. - Hands-on A/B testing experience for evaluating model and policy changes. - Proven ability to lead technical teams while staying involved in model development, paired with clear stakeholder communication and sound business judgment.

Nice to have - Familiarity with Southeast Asian credit markets, bureaus, and alternative data providers. - Experience with MLflow or comparable production ML tooling. - Understanding of IFRS 9 and regional credit regulations across multiple markets.

Benefits and work setup - Competitive compensation tied to experience and location, with equity participation. - Opportunity to shape a growing data science and credit risk function within a global, mission-driven fintech environment. - Modern ML stack and cloud infrastructure, with a globally distributed team setup.