Credit Loss Manager

inDrive Money is seeking an Expected Credit Loss Manager to support the development, enhancement, and monitoring of credit risk models and impairment methodologies. In this role, you will be responsible for ECL calculation and reporting in line with IFRS 9/US GAAP requirements, development and validation of PD/LGD/EAD models, portfolio risk analysis, and optimization of risk reporting processes to support effective risk management and regulatory compliance.

Calculation and monitoring of Expected Credit Losses (ECL) in accordance with IFRS 9 requirements
Support and enhancement of IFRS 9 impairment methodologies, models, and related documentation
Development, validation, and monitoring of risk parameters including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD)
Performing back-testing, sensitivity analysis, and stress testing of credit risk models
Participation in internal and external audit processes, including preparation of supporting documentation and explanations
Preparation of regular risk and impairment reports for management, regulatory, and financial reporting purposes
Conducting ad-hoc portfolio analysis and identifying key credit risk trends
Automation and optimization of reporting and risk calculation processes
Support and development of credit risk management policies, methodologies, and procedures
Collaboration with finance, risk, analytics, and regulatory teams on credit risk and provisioning topics

2+ years of experience in credit risk, IFRS 9, risk analytics, or financial risk management
Strong understanding of IFRS 9 impairment methodology and ECL calculation principles
Experience with PD, LGD, and EAD modeling approaches
Understanding of model validation, stress testing, and back-testing techniques
Strong analytical and quantitative skills
Advanced SQL skills and practical experience with Python, SAS, R, or similar analytical tools
Experience working with large datasets and financial reporting processes
Knowledge of banking products and credit risk metrics