Head of Data Science

About the Company

Our client is a Singapore-listed financial technology company operating across Southeast Asia, with a strong presence in the Philippines, Vietnam, and Thailand. They are scaling rapidly and transforming financial services through data-driven innovation and machine learning.

With a 100+ person data team and a commitment to advanced analytics, they are building world-class capabilities in credit risk, fraud detection, and customer intelligence across emerging markets.

About the Role

We are seeking an experienced and driven Head of Data Science to lead data science and machine learning efforts across three fast-growing international markets: Philippines, Vietnam, and Thailand.

This is a senior leadership role at the intersection of advanced analytics, credit risk modeling, and regional business strategy. You will build and guide a centralized team of 5 data scientists based in Singapore, own end-to-end development of credit risk models, and establish the foundation for broader ML capabilities that scale across markets.

You will serve as the primary bridge between technical teams and business stakeholders in each country, translating complex data science insights into actionable business strategies.

Key Responsibilities

Team Leadership & Strategy

• Lead and mentor a centralized team of data scientists based in Singapore serving Philippines, Vietnam, and Thailand markets
• Define the data science roadmap aligned with business priorities in each market
• Build a high-performance, collaborative team culture and establish best practices in model development, validation, and deployment
• Manage hiring, onboarding, and career development of data science talent
• Drive a culture of innovation, experimentation, and continuous learning

Credit Risk & ML Model Development

• Own end-to-end design, development, validation, and deployment of credit risk models including: Application risk scorecards Behavioral risk scorecards, Transaction risk models, Default prediction models
• Remain hands-on and lead by example - actively contribute to data analysis, model building, and technical problem-solving alongside the team (50% management, 50% hands-on technical work)
• Expand team capabilities beyond credit risk to include: Fraud detection, Customer segmentation, Churn prediction, Propensity modeling, Lifetime value (LTV) prediction
• Collaborate with ML engineering teams to integrate models into operational systems and data pipelines
• Establish model governance, monitoring, and performance tracking frameworks
• Drive continuous improvement of model accuracy and business impact

Stakeholder Communication & Regional Collaboration

• Act as the primary data science technical point of contact for business stakeholders in Philippines, Vietnam, and Thailand
• Translate complex model outputs and data science insights into clear, actionable recommendations for non-technical audiences
• Regularly present model performance updates, risk insights, and strategic recommendations to senior leadership and country heads
• Work closely with local risk, product, and operations teams to ensure models address real business challenges
• Champion data-driven decision-making across all three markets
• Navigate cross-cultural business environments effectively
• Build strong relationships with regional stakeholders and influence business strategy

Technical Delivery & Innovation

• Drive best practices in feature engineering, model validation, and A/B testing
• Ensure models meet regulatory and compliance requirements across different markets
• Implement MLOps practices for model deployment, monitoring, and retraining
• Stay current with latest developments in ML/AI and identify opportunities to apply new techniques
• Build scalable, maintainable code and modeling infrastructure

Requirements

Essential Qualifications:

• Minimum 10 years of experience in data science, machine learning, or advanced analytics
• At least 3-5 years in a team leadership or people management role
• Deep domain expertise in credit risk modeling and/or the financial services industry (lending, banking, fintech, digital lending, BNPL, or similar)
• Proven track record of building and deploying credit scorecards (application scorecards, behavioral scorecards, PD/LGD models)
• Strong technical skills across the full data science lifecycle: Data analysis and exploration, Feature engineering, Model development (logistic regression, gradient boosting, ensemble methods)Model validation and testing, Production deployment and monitoring
• Hands-on proficiency with: Python (pandas, scikit-learn, XGBoost, LightGBM) SQL and data manipulation, Statistical analysis and hypothesis testing, ML model deployment and MLOps
• Excellent communication and stakeholder management skills, with the ability to: Explain complex technical concepts to non-technical audiences. Present to C-level executives and senior leadership . Influence business decisions with data. Navigate cross-cultural business environments
• Proven people management experience: hiring, mentoring, performance management, and team building
• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or related quantitative field (Master's or PhD preferred)

Preferred Qualifications:

• Experience working in Southeast Asian financial markets, particularly Philippines, Vietnam, or Thailand
• Knowledge of regulatory requirements for credit risk modeling in emerging markets
• Experience with alternative data and open banking for credit decisioning
• Familiarity with real-time ML systems and online learning
• Experience with fraud detection, customer analytics, or other ML use cases beyond credit risk
• Background in consumer lending, microfinance, BNPL, or digital lending
• Experience scaling data science teams in high-growth environments
• Publications, patents, or contributions to open-source ML projects

What We Offer

Impact & Ownership

• Lead a high-impact data science function across three fast-growing markets in Southeast Asia
• Shape the ML strategy from the ground up - real ownership and influence over how models are built and applied
• Play a key role in building and shaping the data science team itself
• Direct impact on business decisions affecting millions of customers

Growth & Development

• Work with a passionate, cross-functional team that values data-driven thinking and experimentation
• Access to cutting-edge tools, technologies, and infrastructure
• Opportunity to expand beyond credit risk into broader ML applications
• Career progression opportunities within a rapidly scaling organization

Compensation & Benefits

• Competitive salary package commensurate with experience
• Performance-based bonuses
• Comprehensive medical and insurance coverage
• Professional development budget
• Flexible work arrangements

Work Arrangements

• Based in Singapore
• Travel required: Jakarta monthly and Bangalore quarterly (can be discussed)
• Mix of remote and office work (hybrid model)