Lead - Credit Risk Modelling - Consulting

Job location: [{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mumbai","addressCountry":"IN"}}] Work arrangement: Employment type: FULL_TIME Salary: "" Experience requirements: {"monthsOfExperience":84,"educational":{"credentialCategory":"bachelor degree"}} Education requirements: "" Lead - Credit Risk Modelling - Consulting Role: - The Company provides specialist advisory services across credit risk modelling, model validation, IFRS 9 implementation, portfolio analytics and regulatory risk management to financial institutions and corporate clients. - Develop and review credit risk models using Excel - based rating agency frameworks, Python and statistical techniques including logistic regression, decision trees and ensemble methods. - Build and enhance IFRS 9 expected credit loss models, including PD, LGD, EAD and CCF components across both simplified and general approaches. - Develop roll - rate - based PD models using customer - level receivables data, portfolio - level data and ageing cohort analysis. - Apply advanced methodologies including TTC - to - PiT conversion, Vasicek modelling, survival PDs and term PD structures. - Conduct credit risk model validations aligned with OCC 2011 - 12 guidance and Basel requirements. - Perform parameter - level validation including WoE, IV analysis, backtesting and out - of - time performance testing. - Evaluate statistical, scorecard and hybrid risk models to ensure analytical integrity and regulatory compliance. - Serve as a subject matter expert in client discussions, supporting solution design, proposal development and project delivery. - Translate client requirements into practical modelling approaches and commercially relevant analytical outputs. - Identify opportunities to expand client engagements through value - added risk advisory solutions. - Support the development of the wider Advisory team's credit risk modelling and validation capability through mentoring, coaching and knowledge sharing. - Create reusable modelling templates, validation frameworks and best - practice guidance to improve consistency and efficiency. - Help colleagues develop expertise in statistical modelling, IFRS 9/ECL methodologies, model validation standards and emerging AI - related risk concepts. Requirements: - 7 - 12 yrs of hands - on experience in credit risk model development, model validation, IFRS 9/ECL modelling, credit analytics or related risk advisory functions. - Strong proficiency in Excel and Python for statistical analysis (logistic regression, decision tree, ensemble methods), model development and validation. - Deep understanding of credit risk methodologies, scorecard development, rating frameworks, model lifecycle management and regulatory model governance. - Demonstrated ability to independently manage complex analytical projects and client engagements. - Strong stakeholder management and communication skills, with the ability to explain complex technical concepts clearly. - Experience in ECL modeling using both simplified and general approaches as per IFRS guidelines. - Experience of TTC to PiT conversion using Vasicek models. - Knowledge of EXCEL and Python libraries for multivariate/ statistical modeling. - Some exposure to AI models in context of credit risk. - Additional experience in stress testing, reverse stress testing and scenario - based portfolio analytics will be preferred.