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Tier-1 brand and Mumbai location increase competition, despite niche regulatory specialization.
Strong regulatory model and banking domain bias reduces cross-industry transferability.
Explicit 2+ years, regulatory model experience, and required programming make shortlisting stringent.
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Support deployment, production, monitoring, validation, audit, governance, and documentation of loss forecasting risk models and analytical frameworks.
Develop and maintain automated production workflows, monitor model outputs, identify performance issues, and ensure adherence to regulatory and governance standards.
Collaborate globally with cross-functional stakeholders to manage model lifecycle activities, including regulatory stress testing and forecasting models such as CCAR, CECL, and DFAST.
Bachelor's degree in Statistics, Mathematics, Economics, Finance, Computer Science, Engineering, Operations Research, or a related quantitative discipline.
2+ years of experience in risk analytics, model validation, model monitoring, model implementation, quantitative analytics, or related fields.
Proficiency in programming languages such as SAS, Python, R, SQL or similar analytical platforms.
Ability to support global operations including coordination across multiple time zones; occasional work outside standard business hours may be required.
Experienced in supporting model production, regulatory frameworks, and governance within risk management environments.
Strong quantitative and programming skills with the ability to independently manage multiple priorities and time-sensitive deliverables.
Operates effectively in a global, fast-paced environment requiring collaboration across geographies and functions, with attention to detail and strong communication skills.