Assistant Vice President- Decision Science

• Undertake model validation activities as dictated by the Global Model Risk Policy including the assessment of model inputs, calculations, reporting outputs, conceptual soundness of the underlying theory and the suitability of the use for its intended purpose, relevance and completeness of data, qualitative information and judgements, documentation, and implementation of the model
• Provide written reports detailing the results of validations highlighting issues identified during the validation
• Validate remediation activities completed by the First line of Defence to ensure appropriate resolution of identified issues
• Work with relevant stakeholders to support the embedding of new Global Model Risk Policies and Procedures
• Provide coaching and guidance to new starters and junior colleagues
• Deliver, high quality, timely validation reports that add value to the business
• Liaise with First line of Defence and other model stakeholders as appropriate to ensure issues have been adequately resolved
• Communicate across technical quantitative, business and strategic levels to ensure that stakeholders understand the implications of model risks and limitations
• Contribute to management, regulatory, and external confidence in all models used across the group

• Minimum 5-10 years of experience of financial model validation/development experience in Risk Management in Wholesale domain
• Proficiency in SAS / R, Python MS Office tools like Excel & PowerPoint
• Proven expertise in using statistical algorithms for solving diverse business challenges and creating significant business value
• Experience of conducting independent model reviews
• Master's / bachelor’s degree in /Statistics/Economic/Mathematics/Engineering/Computer Science/Management or any other quantitative fields of study
• Candidate should have worked on Wholesale Credit models and have good understanding of Wholesale Credit Model Development/Validation
• Candidate should have good understanding of wholesale credit analytics models used for the following areas: Model used for customer selection such as propensity recommendation, customer value, engagement, and experience
• Models used for pricing and measurement of profitability and return and used for automation and operational efficiency of credit decisions
• Wholesale Fraud Analytics model used for fraud detection and reporting using analytics
• Wholesale Credit Decisioning models such as acquisition and behavioural scoring models
• He/she should be able to validate models used for different regulatory perspective such as OCC/FRB, EBA Guidelines and PRA regulations
• Knowledge of internal procedures and local regulations and those of other country regulators would be an advantage
• Candidate should have strong knowledge on Linear/Logistic modelling techniques
• Machine learning techniques good to have

Machine learning techniques

• Continuous professional development
• Flexible working
• Opportunities to grow within an inclusive and diverse environment