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About the role
As the Data & Risk Platform lead, you will lead the core "Data & Decision Layer". Your mission is to build a scalable, explainable, and non-biased credit underwriting system that maximizes lead funnel conversion without compromising risk. You will lead a cross-functional team of data scientists, analysts, and business consultants to evolve our "Intelligent Lending Lifecycle", turning alternative platform data into precise credit decisions. Key Responsibilities ● Platform Leadership: Own the end-to-end "Data & Decision Layer," leveraging platform data to build robust underwriting models within our Business Rule Engine (BRE). ● Intelligent Underwriting: Develop cohort-specific models and alternative data rails to drive precision intelligence in credit assessment. ● Funnel Optimization: Use data-driven insights to improve conversion rates across the lead funnel while maintaining a "Risk-First Architecture". ● Portfolio Vigilance: Implement proactive monitoring, Early Warning Systems (EWS), and real-time oversight to ensure portfolio health. ● Team Orchestration: Lead and mentor a high-performing team of data scientists and analysts to build a comprehensive, long-term risk management system. ● Structural De-risking: Design systems with aligned incentives and cash flow integration to ensure structural stability at scale. Core Competencies ● Business & Tech Balance: Ability to translate complex business risk requirements into scalable technical architectures. ● Clarity & Accountability: A culture-first leader who values direct communication and ownership-driven results. ● Bias for Action: A drive to build and evolve systems in a lean, fast-paced environment. ● Explainability & Ethics: A commitment to building non-biased, explainable AI/ML models for transparent credit decisioning. Must-Have Requirements ● Experience: At least 10 years of relevant experience in data science, risk management, or fintech platform engineering. ● Leadership: Proven track record of leading multi-disciplinary teams (Analysts, Data Scientists, Consultants).
● Domain Expertise: Deep understanding of MSME credit, underwriting workflows, and risk management frameworks. ● Scale Mindset: Experience building and evolving systems that handle high-volume data and real-time decisioning. ● Technical & Mathematical Mastery: Expertise in Mathematics and Statistics (specifically probability, linear algebra, and multivariate analysis) as the foundation for credit modeling. ● AI/ML Proficiency: Knowledge of Machine Learning and Artificial Intelligence frameworks to build predictive models that are not only accurate but also explainable and non-biased.
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