Head Of Data Science & Credit Risk
FINN
WorldwideremotePosted 29 days ago
Skill Required
Data-ScienceCredit-RiskMachine-LearningRisk-ManagementFintechHead-Of-Data-ScienceCredit-Risk-Analytics-DirectorDirector-Of-Credit-Risk-AnalyticsSenior-Data-Scientist-Credit-Risk-ModelingVP-Of-Credit-Risk-and-AnalyticsCredit-Risk-DirectorDirector-Of-Credit-Risk-And-UnderwritingDirector-Data-ScienceMachine LearningStatisticsEngineeringanalyticaldevelopingObservabilityData StructuresanalyticsBigQuerybuildingfintechTestNGMLflowdesignCloudUnitySQLGCPandFulltime
Key highlights
- A competitive salary based on experience and location.
- 10+ years of experience in data science, machine learning, and consumer credit risk.
- Equity participation.
- Experience developing and managing credit policies and portfolios at scale.
Role overview
FINN is a fintech company building simple and transparent financial products for underbanked employees, focusing on wage access, savings, insurance, and fairer financial services. The Head of Data Science & Credit Risk will lead ML-driven underwriting, strengthen risk decisioning across Southeast Asia, and expand into new markets globally. The role combines deep data science expertise with credit risk leadership, building and leading a team to improve approval funnels, portfolio performance, and financial access.
Responsibilities
- Lead the design, testing, and deployment of ML models for credit decisioning, fraud detection, and risk segmentation.
- Develop underwriting algorithms that use alternative data sources to improve risk assessment and expand financial access.
- Build and deploy real-time or near-real-time scoring models that scale across multiple markets.
- Ensure models are interpretable, fair, and robust, with monitoring for accuracy, feature stability, and drift.
- Establish MLOps practices for model versioning, experimentation, deployment, and ongoing monitoring.
- Expand machine learning adoption across the business, including customer value, monetization, and marketing attribution.
- Develop and manage credit risk frameworks, policies, and approval strategies adapted to each market.
- Set risk thresholds and customer segmentation strategies that balance growth, default rates, and portfolio health.
- Monitor key risk metrics, investigate significant changes, and establish early warning signals for portfolio deterioration.
- Simulate policy and model changes, support A/B testing, and refine strategies using performance data and business KPIs.
- Lead stress testing and expected credit loss modeling, partnering with Finance on provisioning and capital allocation.
- Support market expansion through localized risk models and policies aligned with applicable regulatory requirements.
- Build, lead, and mentor a team of data scientists and risk analysts while remaining hands-on with technical work.
- Own the data science and credit risk roadmap, aligning priorities with business growth and expansion plans.
- Communicate model performance, portfolio trends, and strategic recommendations to the executive team and board.
- Partner with engineering, product, and finance to translate analytical insights into measurable business outcomes.
- Evaluate and establish partnerships with alternative data providers and credit bureaus.
- Build a culture of experimentation, accountability, and data-driven decision-making.
- Improve approval rates while maintaining target default rates and responsible lending standards.
- Reduce time-to-decision through automated underwriting and scoring.
- Identify new customer segments and product opportunities through advanced analytics.
- Improve unit economics through risk segmentation and customer value modeling.
- Track the impact of model and policy changes, using feedback loops to improve performance over time.
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.
- Experience developing and managing credit policies and portfolios at scale across multiple products, markets, or both.
- A proven track record of building, deploying, and monitoring production ML models within real-time or near-real-time decisioning pipelines.
- Hands-on experience with experimentation and A/B testing to evaluate model and policy changes.
- Strong statistical and mathematical skills, with expertise in both classical statistical methods and modern machine learning.
- Strong working knowledge of SQL and exploratory data analysis, alongside experience with cloud data platforms.
- Experience building and leading technical teams while remaining actively involved in model development and problem-solving.
- Strong communication skills, with the ability to explain complex models and credit risk concepts clearly to business stakeholders.
- Sound business judgment and the ability to connect technical decisions to growth, portfolio performance, and return on investment.
- An adaptable, proactive approach to working in a fast-paced startup environment.
Nice to have
- Familiarity with Southeast Asian credit markets, credit bureaus, and alternative data sources.
- Experience with MLflow or similar frameworks for production model development and deployment.
- Understanding of IFRS 9 and local credit regulations across multiple markets or regions.
Benefits
- 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 opportunity to help redefine financial services for underbanked employees.
- Meaningful Impact: Build models that expand financial access for underbanked employees.
- Greenfield Opportunity: Shape our ML and risk capabilities from the ground up.
- Modern Technology: Work with a modern ML stack and cloud infrastructure.
- Rapid Growth: Lead a core function as FINN scales into new markets.
- Mission-Driven Work: Help improve financial well-being through fairer, more accessible financial services.