Job Title: Senior Vice President - Model Risk & Quantitative Analytics

Location: Gurgaon, India

Experience Required: 15+ years in quantitative risk management (banking / financial services preferred)

Reports to: Chief Risk Officer / Head of Model Risk Management

Role Summary

The Senior VP will lead the Model Risk function for Markets and Treasury, overseeing the end-to-end validation, revalidation, and governance of all liquidity, pricing, and risk models (including stress models). This role requires deep expertise in liquidity risk, model risk, derivative pricing, and strong programming capabilities to drive automation and best practices. The individual will act as the key escalation point for material risk appetite breaches, policy deviations, and model failures, while collaborating with global risk, business, and technology teams.

Core Capabilities :

Customer Focus - Align model risk practices with business and regulatory expectations.

Plans and Aligns - Lead strategic roadmaps for model validation cycles and technology investments.

- Cultivates Innovation - Drive adoption of advanced analytics (AI/ML, cloud-based validations) and programming efficiencies.

Technical & Leadership Mastery

- Deep understanding of liquidity risk (LCR, NSFR, stress testing) and model risk (SR 11-7, local regulatory standards).

- Strong financial and numerical literacy across traded and non-traded market risk.

- Extensive experience in derivatives pricing models (e.g., IR, FX, Credit) and model validation for complex risk systems.

- Expert-level proficiency in Python, C++, or C# - ability to guide teams in production-level validation libraries.

Key Accountabilities :

Validation & Implementation Oversight - Lead validation of all Markets & Treasury models (liquidity, pricing, risk, stress), both internally developed and vendor models, ensuring robust sign-off before and after implementation into technology assets.

Periodic Revalidation - Establish and govern a risk-based revalidation schedule for all models across Markets & Treasury, ensuring timely completion and remediation of findings.

Risk Appetite & Escalation - Ensure any prospective risk appetite breaches, material losses, or deviations from the Model Risk Policy/Framework are immediately known to relevant Domain-aligned teams and escalated to the Board Risk Committee as needed.

Cross-functional Leverage - Proactively leverage specialist skills from Risk, Treasury, Front Office, and Technology teams to close model risk gaps and drive enterprise-wide model risk culture.

Regulatory & Audit Management - Lead interactions with RBI, SEBI, and internal audit on model risk matters; represent the bank in regulatory inspections and benchmarking exercises.

Team Development - Build and mentor a high-performing team of quantitative analysts and validators based in Gurgaon and global hubs.

Experience & Qualifications

Experience

- 15+ years of progressive experience in quantitative risk management at a bank, financial institution, or regulatory body.

- At least 8 years in a leadership role overseeing model validation for liquidity, market risk, or derivative pricing.

- Proven track record of managing model risk policy and independent validation teams across multiple asset classes.

Qualification Requirements

- Postgraduate degree (PhD strongly preferred) in Mathematics, Financial Engineering, Statistics, Physics, or equivalent quantitative discipline.

- Professional certifications (e.g., FRM, PRM, CFA) are highly desirable.

Technical Requirements

- Advanced programming experience (Python, C++ or C#) for model benchmarking, validation frameworks, and automation.

- Deep familiarity with regulatory model risk expectations (Basel, SR 11-7, EBA guidelines, RBI's draft model risk framework).

Why Join This Role?

Leadership Impact - Shape the model risk governance for a major Markets and Treasury business.

Regulatory Visibility - Work directly with global regulators and senior executives.

Gurgaon Location - Lead a growing centre of excellence in a strategic hub for risk analytics.