Head, Credit Modelling

TNG Digital Sdn Bhd; Kuala Lumpur; On-site; MYR 180,000 - 340,000; Full time

Job summary

TNG Digital Sdn Bhd in Kuala Lumpur seeks a senior leader to architect end-to-end credit risk modelling across acquisition, growth, fraud detection and limit management. You will own the modelling roadmap, drive full lifecycle development, and ensure scalable, compliant deployment with automated monitoring.

You will partner with Product, Risk and Tech to translate model outputs into risk-based pricing and decisioning, enabling data-driven growth across BNPL and digital lending initiatives.

Qualifications

• 6+ years in credit-risk modelling or risk analytics with leadership experience.
• Experience in consumer finance, BNPL, digital lending, or retail banking.
• Strong command of ML algorithms and data science tooling.
• Hands-on with Python, R, SQL; familiarity with data platforms and deployment.
• Deep knowledge of PD/LGD/EAD, Vintage, NCL, Roll Rate; governance experience.

Responsibilities

• Architect and own end-to-end modelling roadmap for consumer credit scenarios.
• Lead full lifecycle model development from data sourcing to production deployment.
• Establish monitoring for AUC, KS, approval rate, retention, and delinquency.
• Govern model lifecycle, validation, back testing, and regulatory compliance.
• Partner with product to embed model-driven insights into credit and limit management.

Skills

Credit risk modelling

Leadership

Machine learning

Python

R

SQL

Hive

Presto

Spark

MLOps

API deployment

PD/LGD/EAD

Vintage

Roll Rate

Regulatory compliance

Fraud detection

Real-time risk systems

Education

Bachelor's degree in Mathematics, Statistics, Computer Science, Financial Engineering, or Economics

Master's or PhD preferred

Tools

Hive

Presto

Spark

Job description

# Head, *Credit Modelling*Kuala Lumpur, MalaysiaPermanent#### Duties & Responsibilities* 1. Modelling Framework & Systemization* Architect and own the end-to-end modelling roadmap for consumer credit scenarios, including acquisition and growth scoring, fraud detection, new-to-credit scoring, limit pricing, behavioural, and collection models.* Lead full-lifecycle model development — from data sourcing and feature engineering to algorithm development, validation, and production deployment — ensuring scalability, modularity, and automation.* Establish a robust monitoring framework to track AUC, KS, approval rate, conversion, retention, and delinquency metrics; proactively flag deviations and implement optimization.* Govern all model lifecycle processes, including versioning, documentation, validation reports, back testing, and compliance with regulatory requirements.* 2. Product & Strategy Integration* Partner with product teams to integrate model-driven intelligence into credit, instalment, and limit management journeys from the design stage.* Design automated decisioning strategies based on model outputs (e.g., risk-based pricing, approval segmentation, dynamic limit adjustments).* Define and align data collection, event tracking, and input quality standards for model readiness.* Run A/B experiments and champion test–learn–scale loops to quantify the business and risk impact of different strategies.* Lead pre-launch risk assessment for new products or channels, building early-warning and fraud-prevention models.* 3. Risk Operations & Business Partnership* Work closely with operations to enhance segmentation, collection prioritization, and resource allocation using model insights.* Monitor key credit-risk metrics such as approval rate, disbursement volume, NCL, Roll Rate, and Vintage curves.* Identify anomalies (e.g., abnormal user segments or regional concentration) and drive risk mitigation strategies.* Build and maintain unified risk dashboards and reporting frameworks reflecting real business dynamics.* Support multi-market teams (Indonesia, Philippines, Thailand, etc.) with localized modelling and monitoring frameworks.* 4. Leadership & Cross-Functional Delivery* Lead and mentor a cross-functional modelling team (data scientists, analysts, engineers), building both technical excellence and business acumen.* Manage project prioritization, progress tracking, and quality assurance for all modelling initiatives.* Strengthen collaboration with Product, Risk, and Tech teams to accelerate model implementation and strategy execution.#### Requirements* Bachelor’s or above in Mathematics, Statistics, Computer Science, Financial Engineering, or Economics; Master’s or PhD preferred.* 6+ years of experience in credit-risk modelling or risk analytics, with at least 3 years in a leadership role.* Proven track record in consumer finance, BNPL, digital lending, or retail banking.* Strong command of machine learning algorithms (Logistic Regression, GBDT, XGBoost, LightGBM, CatBoost, Neural Networks).* Proficient in Python, R, SQL; hands-on with data platforms such as Hive, Presto, Spark; MLOps or API-based deployment experience is a plus.* Deep understanding of PD/LGD/EAD, Vintage, NCL, and Roll Rate metrics.* Experience in model validation, governance, and regulatory compliance.* Strong business mindset — capable of translating model insights into product and strategy impact.* Experience in online real-time risk control systems, fraud detection, and dynamic credit engines is preferred.