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Tier-1 brand, metro location, mid-level ML management and popular GenAI skillset increase candidate competition.
Advanced ML skills transfer across industries, but banking-specific risk and regulatory experience reduces portability.
Explicit 5+ years requirement, leadership expectation, and regulated banking environment make filters strict.
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Manage a team developing foundation models, Gen AI, and Agentic AI applications across multiple bank business lines.
Oversee operational risk mitigation, capital requirement computations, resource allocation, and regulatory interactions.
Lead strategy development for models, methods, and research with responsibility for implementation, mentoring, and hiring within quantitative analytics and credit risk teams.
5+ years of quantitative analytical experience.
2+ years of leadership experience.
Master's degree or higher in quantitative discipline (mathematics, statistics, engineering, physics, computer science).
Work Experience Required: At least 5+ years in quantitative analytics and 2+ years leading teams, with experience in AI/ML model development strongly preferred.
Experienced in building and deploying Foundation Models, Gen AI, and Agentic AI applications at enterprise scale.
Strong quantitative, data engineering, and AI/ML skills with ability to lead AI infrastructure, model optimization, and multi-agent system development.
Ability to manage operational risk and compliance with enterprise governance in a regulated financial environment.