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.

Skills: management,risk,decisioning,risk management,underwriting,models,data,credit