Credit Card - Specialist, Credit Risk & Portfolio Optimization

Job Title: Credit Cards - Specialist, Credit Risk & Portfolio Optimization

Location: Colombo, Sri Lanka

Experience: 8-10 Years

Project Duration: 5 months

Indicative compensation range: INR 12-15 Lakhs for the project duration. Certain actuals including travel expenses will be reimbursed. Salary will not be a constraint for the right profile. Logistical support will be provided for a smooth experience.

Role Overview

This is a contractual role in the Credit Card domain for a project of 5 months at Colombo. As a Data Science expert, you will spearhead the development of advanced statistical models to manage credit risk and drive portfolio growth for a leading bank in Sri Lanka. This role requires a blend of technical mastery in predictive modelling (PD/LGD/EAD) and strategic insight to optimize credit card spends and engagement.

Core Responsibilities

• Model Development: Behavior scorecards, including PD, LGD, and EAD models.
• Forecasting & Analytics: Loss-forecasting frameworks using Vintage, Markov, and Machine Learning (GBM/GLM) approaches.
• Feature Engineering: Extract insights from bureau, transactional, device, and alternative data with rigorous quality control.
• Validation & Governance: Perform back testing (KS/AUC) and stability monitoring (PSI/CSI) while ensuring model explain ability via SHAP/Reason Codes.
• Portfolio Optimization: Develop data models to drive credit card spends, merchant targeting, and cross-border campaign recommendations.
• Regulatory Alignment: Ensure models comply with IFRS 9 / CECL accounting standards and Basel capital frameworks.

Technical Skills & Qualifications

• Masters in Statistics or Economics from a top-tier institution.
• Proficiency in Python, SQL, SAS, and Tableau.
• Deep understanding of the Credit Card Lifecycle and portfolio interventions.
• Hands-on experience with Machine Learning applied to credit risk.
• Expertise in IFRS 9 / CECL (Lifetime ECL, staging, and pooling).
• Ability to translate complex algorithmic outputs into clear business strategies for non-technical stakeholders.