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Tier-1 brand, metro location and mid-level experience band concentrate candidate competition despite niche quant requirements.
Requires deep banking risk and regulatory expertise, limiting transferability across industries.
Explicit 2-5 years and mandatory quant, regulatory, and Python skills create high shortlisting strictness.
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Develop and maintain high-quality risk analytics models for Market Risk and Counterparty Credit Risk including capital market models for FX, Interest Rate Derivatives, securities lending, fixed income, and securitized products.
Ensure regular production of analytical outputs such as daily trading limit models, Initial Margin models for uncleared trades, and Basel regulatory exposure (EAD) calculation tools; collaborate with front office, regulators, Audit, and other reviewers.
Support stress testing, capital quantification, internal capital allocation, and ensure model approaches comply with corporate and regulatory requirements like BASEL, CCAR, and SR11/7.
2-5 years of hands-on market/counterparty quantitative risk experience.
Master's degree in Statistics, Economics, Mathematics or advanced quantitative degree; or B.Tech from Tier 1 college with MBA in related field.
Proficiency in Python (preferred), SAS, advanced Excel, and VBA programming; experience in building stochastic pricing and Monte Carlo simulation models.
Strong regulatory knowledge of banking capital rules, market risk rules, and model risk compliance (BASEL, CCAR, SR11/7).
Experienced in quantitative risk modelling with deep understanding of market and counterparty credit risk frameworks and Basel capital regulations.
Capable of working independently on complex risk analytics and engaging with multiple stakeholders including senior management and regulatory bodies.
Strong quantitative and technical skills with experience in programming (Python preferred) and model development or validation, comfortable in a global, multi-cultural environment.