Head of Data Science, Credit Risk
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Job Description
Head of Data Science leading ML-driven underwriting strategy at FINN, enhancing financial inclusion in Southeast Asia. Develop risk models and manage data science teams for optimal growth.
Responsibilities:
- Design and implement advanced ML models for credit decisioning, fraud detection, and risk segmentation
- Lead development of next-generation underwriting algorithms using alternative data sources
- Build and deploy real-time scoring models that scale across multiple markets
- Champion model interpretability and fairness in AI-driven credit decisions
- Drive machine learning adoption across the organization - eg. experimentation on customer-value and monetization models, marketing attribution solutions.
- Establish MLOps best practices for model versioning, monitoring, and deployment
- Develop comprehensive credit risk frameworks adapted to each market's unique dynamics
- Design approval strategies and risk thresholds that optimize for growth and portfolio health
- Create early warning systems for portfolio deterioration using predictive analytics
- Lead stress testing and expected credit loss modeling initiatives
- Partner with Finance on provisioning and capital allocation strategies
- Build and mentor a high-performing team of data scientists and risk analysts
- Drive data science roadmap aligned with business expansion goals
- Present risk insights and recommendations to executive team and board
- Establish partnerships with alternative data providers and credit bureaus
- Foster a culture of experimentation and data-driven decision making
- Optimize approval rates while maintaining target default rates
- Reduce time-to-decision through model automation
- Identify new customer segments and product opportunities through advanced analytics
- Support market expansion with localized risk models and regulatory compliance
- Drive unit economics improvement through sophisticated segmentation
Requirements:
- 10+ years combined experience in data science/ML and consumer credit risk in FinTech, digital lending, or BNPL/EWA products
- Experience developing and managing credit policies and portfolios at scale - either multi-product, multi-market, or both
- Proven track record building and deploying production ML models as part of real-time or near-real-time decisioning pipelines with experimentation (A/B testing).
- Expertise in SQL/exploratory data analysis, and experience with cloud platforms (we use GCP BigQuery but direct/specific experience is not necessary)
- Experience building and leading technical teams while remaining hands-on
- Excellent communication skills to translate complex models to business stakeholders.
- Familiarity with Southeast Asian credit markets and alternative data sources
- Knowledge of MLFlow or similar production-grade model development deployment frameworks
- Broad understanding of regulatory requirements in various markets/regions (IFRS 9, local credit regulations)
Benefits:
- Competitive salary based on experience and location
- Equity participation
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