Vice President; Structurer

DUTIES: Develop and implement quantitative modeling frameworks to design, evaluate, and optimize systematic equity volatility strategies, leveraging time-series analysis, statistical modeling, machine learning techniques, and regime-switching approaches. Research, construct, and evaluate equity volatility-based strategies, including yield-oriented volatility alpha and relative value strategies, utilizing index options, single-stock options, and volatility-linked derivatives to achieve defined risk-return objectives. Design and implement quantitative hedging strategies and portfolio hedging solutions to deliver targeted downside protection under adverse market conditions while optimizing carry costs and risk-adjusted performance. Conduct scenario analysis, stress testing, and performance attribution to assess strategy robustness, portfolio behavior, and risk exposures across varying market environments. Develop and maintain quantitative research tools, models, and analytics pipelines for back-testing, market risk analysis, and process automation using Python and related analytical frameworks. Support the development and positioning of equity derivatives solutions for institutional clients by delivering quantitative insights, modeling outputs, and risk analytics through client-facing dashboards and marketing materials. Collaborate with cross-functional teams, including sales, trading, and risk, to translate business objectives into quantitative modeling and analytics solutions, and educate stakeholders on existing offerings and new strategies. Remote work may be permitted within a commutable distance from the worksite.REQUIREMENTS: Master's degree or equivalent in Financial Engineering, Statistics, Finance, or related: and 3 years of experience in the job offered or a related Finance occupation. Must include 3 years of experience in each of the following: Utilizing advanced quantitative modeling and data science principles, including timeseries analysis, machine learning, and deep learning, to develop quantitative forecasting frameworks for volatility driven risk, drawdowns, and adverse portfolio outcomes; Applying statistical, econometric, and predictive analytics techniques to largescale financial datasets to extract insights, identify trends, quantify risk exposures, and assess portfolio level performance across different market regimes; Developing, back testing, and evaluating quantitative forecasting and portfolio analytics models, including scenario analysis and performance attribution, using Python in a production research environment; Designing and developing endtoend quantitative research and analytics infrastructure, including data ingestion pipelines, feature engineering processes, and scalable simulation environments to enable robust risk analytics and quantitative strategy evaluation; and, Supporting risk management, and investment decision making by translating business objectives into actionable quantitative modeling solutions through collaboration with cross functional stakeholders. Requisition 26033855. If interested apply online at www.bankofamerica.com/careers or email your resume to [email protected] and reference the job title of the role and requisition number. No phone calls. EOE.