Lead Quantitative Analytics Specialist

Lead development, documentation, validation, and governance of quantitative models for Securities Based Lending (SBL) in Wealth and Investment Management (WIM).

Advance model-based capabilities for lending and maintenance margin decisions across diverse financial products and lending strategies.

Collaborate with stakeholders across business, risk management, model validation, audit, and technology to influence strategic modeling decisions and support quantitative modeling framework evolution.

5+ years of Quantitative Analytics experience or equivalent via work experience, training, military service, or education.

Bachelor's degree or higher in mathematics, statistics, engineering, physics, economics, computer science, or related quantitative discipline.

Proficiency in Python, SQL, and GitHub programming.

Strong understanding or experience with quantitative risk modeling methods including Value-at-Risk (VaR), Expected Shortfall (ES), stress testing, and scenario analysis is implied but not explicitly mandated.

Demonstrated expertise in Securities Based Lending modeling with experience in collateral risk management and lending portfolio analytics.

Proven ability to handle complex financial instrument modeling including equities, fixed income, structured products, and digital assets.

Experienced in delivering high-impact modeling solutions with strong ownership, effective communication, and collaborating across business, risk, and technology teams in a regulated financial environment.