Role Overview:

As an Assistant Vice President within the Risk Methodology group, you will spearhead the development, implementation, and validation of complex market risk models with a primary focus on the Fundamental Review of the Trading Book (FRTB).

You will operate at the intersection of quantitative finance and regulatory compliance, collaborating closely with Front Office trading desks, Model Risk Management, and global regulatory reporting teams.

Your work will be instrumental in ensuring the firm maintains robust capital adequacy standards while optimizing risk-weighted assets.

By translating intricate regulatory requirements into scalable quantitative frameworks, you will directly influence the firms strategic risk appetite and ensure seamless adherence to evolving global banking standards.

Key Responsibilities:

- Design and implement advanced quantitative models for Internal Models Approach (IMA) and Standardized Approach (SA) under FRTB guidelines to ensure regulatory compliance and accurate capital calculation.

- Partner with technology and data engineering teams to enhance the data infrastructure, ensuring that risk inputs meet the stringent requirements for P&L attribution and backtesting.

- Lead the model documentation process for internal and external audits, providing clear technical justifications to satisfy regulatory scrutiny and internal model governance standards.

- Collaborate with trading desk heads to analyze the impact of FRTB implementation on business strategy, providing actionable insights that balance risk mitigation with commercial objectives.

- Mentor junior quantitative analysts by providing technical guidance on stochastic calculus, time-series analysis, and numerical methods to foster a high-performance research culture.

Required Skillset:

- Demonstrate deep expertise in market risk modeling, specifically regarding VaR, Expected Shortfall, and the nuances of the FRTB framework, supported by a strong foundation in quantitative finance.

- Exhibit proficiency in programming languages such as Python, C++, or R to build, test, and deploy complex financial models within a high-frequency data environment.

- Communicate highly technical risk concepts to non-technical stakeholders and senior management with clarity, ensuring alignment across diverse business functions.

- Possess an advanced degree in Financial Engineering, Mathematics, Statistics, or a related quantitative discipline from a premier institute.

- Adapt seamlessly to a hybrid work environment in Mumbai, maintaining high levels of productivity and collaborative engagement across global time zones.