Manage internal team and client stakeholders 

Provide thought leadership, develop, and execute comprehensive modeling strategies aligned with business objectives and industry best practices. 

Design, develop, and validate Pillar 1 IRB capital, IFRS 9 provision, pillar 2 stress testing (internal and/or regulatory) and BAU decisioning models, ensuring accuracy, reliability, and compliance with regulatory standards. Conduct rigorous testing and validation methodologies to ensure model robustness and reliability. 

Assess regulatory compliance covering the key regulations and across multiple jurisdictions – PRA SS 1/23, PRA SS 11/13, EBA GLs and RTS covering the IRB roadmap, IFRS 9 regulatory and audit expectations, regulatory and internal ICAAP stress test related guidelines covering jurisdictions like UK, Europe, US and Hong Kong 

Provide support to banks in implementing the model risk management framework as per regulatory requirements for 1st and 2nd line teams 

Provide analytical support for recommending actions to mitigate risk and use judgment-based decision-making regarding policies and procedures. 

Assess the quality of the data for model development/validation as well as inputs to the model, providing recommendations to improve the data quality at the source. 

Lead, train, and mentor junior members in the team, providing guidance, support, and fostering a collaborative and innovative team culture. 

Propose recommendations to improve monitoring systems and capabilities based on identified risk and control gaps. 

Remain up to date with the evolving regulatory landscape related to credit risk and contributing to the creation of whitepapers. Researching and contributing to artifacts creation as required in a consulting role. 

Build and maintain strong relationships with client stakeholders (at all levels of seniority). 

Internal and client team management, program management, driving project delivery, delivery ownership, identifying sales opportunities etc. 

Relevant experience in developing, validating models and risk management of retail credit risk models (IRB, IFRS 9, stress testing, Decisioning scorecards) 

Knowledge of various statistical techniques and proven skill in regulatory and non-regulatory credit risk modelling 

Understanding and experience on the regulatory risk model development/validation guidelines – PRA SS 1/23 and SR 11-7 and model risk management, Pillar 1 credit risk capital regulatory requirements covering multiple jurisdictions including PRA, EBA, ECB, HKMA, CBUAE, and Basel III finalization and its regional adaptations, Regulatory and internal stress tests for UK, Europe, and US, CECL and IFRS 9 regulatory and audit requirements etc.  

End-to-end development or independent validation of credit risk and regulatory models including but not limited to – PD, LGD, EAD, Stress Testing, IFRS 9, CECL, Credit Scorecards, etc. 

Good business acumen with the knowledge of finance, business or regulatory submission processes 

Consulting skills – Program management, team management, client stakeholder management,  

Good know-how of different phases of model development and/or validation life cycle. 

Hands on expertise in SQL, SAS, Python, R and working with large data sets. 

Educational qualification with an analytical or quantitative background (Engineering/ Finance/Management/Statistics/Economics/Data Science etc.) 

Strong model documentation/model validation report writing skills 

Strong communication/presentation skills – written & verbal. 

Strong proficiency in developing PowerPoint presentation, advanced excel, and report writing. 

Lead projects and teams - provide thought leadership, technical guidance, training, and oversight.  

Advanced Degree: Master’s/PhD in Finance, Economics, Statistics, Data Science, or similar. 

 Certifications: FRM, CFA, PRM, or equivalent. 

Credit Risk Modeling: Experience with PD, LGD, EAD, IFRS 9, CECL, and stress testing. 

Regulatory Knowledge: Familiarity with PRA, ECB, EBA, HKMA, CBUAE, Basel III. 

 Model Development/Validation: End-to-end experience with model development/validation lifecycle. 

Technical Skills: Proficiency in SQL, SAS, Python, R. 

 Data Management: Experience handling large datasets for modeling. 

Consulting/Project Management: Stakeholder and team management. 

 Communication Skills: Strong report writing and presentation skills. 

 Leadership: Ability to lead teams, provide technical guidance, and mentor.