Senior Analyst - Quantitative Credit Risk

Job Summary: Credit Risk Modelling Analyst will be responsible to manage the model implementation cycle (from design, implementation, monitoring to demise) of Credit risk, Fair Lending and IFRS9 models covering the Large corporates, Mid-market and SME portfolios along with Banks / FIs and Sovereign portfolio. Job Description: - Involve in model development, model validation, model recalibration and monitoring model documentation and maintain the risk model inventory. - Performing these activities on the MRM framework for corporate BASEL and IFRS9 models. - Lead credit scoring modelling exercise with applicable compliance to regulations. - Validating Fair Lending Models and suggesting recommendations for enhancements. - Implementation and enhancement of ECL models based on internal enhancements, BASEL or Saudi Central Bank regulatory stipulation. - Working closely with BA's and system owners for model development. - Strong understanding of data analytics and enterprise-level data architecture, which is used to consolidate model development and model monitoring information. - Support business reporting and analytics function in generating bespoke reports from credit approver and rating system. Key Requirements: - 3+ Years of experience in model development, model validation and model management. - Understanding of Stress testing/ sensitivity testing - Good Understanding of Fair Lending models/ ML Model techniques and tests - Experience in risk requirements as related to scorecards and IFRS9/ CECL/ HMDA - Fair Lending. - Strong understanding of credit risk and model development/validation. - In-depth knowledge of model development and validation, including data extraction and pre-processing, modular model development, user acceptance testing and model performance assessments of: - IFRS9 models: staging, PD, EAD, LGD - Risk scorecards and frameworks - Large corporates, Mid-market and SME portfolios. - Credit decisioning and Early Warning Risk Models - Good programming skills in Python. Transferrable knowledge from R or SAS. - Knowledge of SAS EG and ECL will be an added advantage.