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Tier-1 bank brand but niche securities-based lending quant specialization limits broad applicant density.
Specialized SBL, regulatory risk, and portfolio risk methodologies require deep financial services domain expertise.
Explicit 5+ years, mandatory quant modeling expertise, and Python/SQL/GitHub requirements create strict shortlisting filters.
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Develop, enhance, and govern quantitative models for Securities Based Lending (SBL) within Wealth and Investment Management (WIM).
Lead initiatives involving model creation, implementation, validation, and documentation across diverse financial products and lending strategies.
Collaborate with stakeholders including risk management, audit, technology teams, and regulators to influence strategic modeling decisions and ensure model governance.
5+ years of Quantitative Analytics experience or equivalent demonstrated via work experience, training, military experience, or education.
Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Proficiency in Python, SQL, and GitHub programming skills.
Experience or demonstrated expertise in quantitative modeling within financial services, specifically securities-based lending modeling, is expected but not strictly mandatory.
Experienced in advanced quantitative risk methodologies including Value-at-Risk (VaR), Expected Shortfall (ES), stress testing, and scenario analysis within financial services.
Ability to lead complex, high-impact modeling projects and make decisions under ambiguity with strong accountability and ownership.
Strong collaboration and communication skills to translate quantitative concepts for executive stakeholders and work closely across business, risk, and technology functions.