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Tier-1 brand, metro location, mid-level title, but niche quant skillset limits applicant pool.
Specialized securities-based lending and risk modeling require finance-domain expertise, limiting cross-industry transferability.
Explicit 5+ years, domain-specific quant modeling and GitHub/Python requirements make filters strict.
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Lead development, validation, and governance of quantitative models for Securities Based Lending (SBL) in Wealth and Investment Management.
Advance firm’s modeling capabilities in lending and maintenance margin decision-making across diverse financial products and strategies.
Collaborate with business, risk, validation, audit, and technology teams to influence strategic modeling decisions and support quantitative modeling framework evolution.
Minimum 5+ years of Quantitative Analytics experience or equivalent combination of experience, training, military service, or education.
Bachelor's degree or higher in quantitative discipline (mathematics, statistics, engineering, physics, economics, or computer science).
Proficiency in Python, SQL, and GitHub programming skills.
Work Experience Required: Minimum 5+ years in Quantitative Analytics.
Strong expertise in Securities Based Lending modeling including risk methodologies like VaR, Expected Shortfall, stress testing, scenario analysis.
Experienced with broad range of financial product modeling including equities, fixed income, structured products, digital asset products, and collateral risk management.
Demonstrated ability to lead complex modeling projects with accountability and collaborate effectively across business, risk, and technology stakeholders.