VP-level Quant Structurer - Equity Volatility (Remote)

Bank of America; New York (NY); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Bank of America seeks a seasoned quantitative researcher to design and implement volatility-driven strategies and risk analytics for institutional clients. You will build end-to-end modeling frameworks, back-testing pipelines, and risk analyses using Python within a collaborative, cross-functional environment.

The role emphasizes advanced timeseries modeling, ML/deep learning techniques, and strong communication to educate stakeholders on quantitative offerings and new strategies.

Qualifications

• Master's degree in Financial Engineering, Statistics, Finance, or related field.
• 3 years of experience in the job offered or a related Finance occupation.
• Three years of experience in advanced quantitative modeling and data science principles including timeseries analysis, ML and deep learning.
• Experience applying statistical, econometric, and predictive analytics to large financial datasets.
• Experience developing, back testing, and evaluating quantitative forecasting and portfolio analytics models using Python.

Responsibilities

• Develop and implement quantitative modeling frameworks to design, evaluate, and optimize systematic equity volatility strategies using time-series analysis and ML techniques.
• Research, construct, and evaluate volatility-based strategies using index options, single-stock options, and volatility-linked derivatives.
• Design and implement quantitative hedging strategies and portfolio hedging to deliver downside protection and optimize carry costs.
• Conduct scenario analysis, stress testing, and performance attribution to assess robustness and risk exposures.
• Develop and maintain quantitative research tools, models, and analytics pipelines for back-testing and risk analysis using Python.
• Support equity derivatives solutions for institutional clients by delivering quantitative insights and risk analytics through dashboards and marketing materials.
• Collaborate with sales, trading, and risk to translate business objectives into quantitative analytics solutions.

Skills

Timeseries analysis

Machine learning

Deep learning

Quantitative forecasting

Risk analytics

Education

Master's degree in Financial Engineering/Statistics/Finance

Tools

Python

Backtesting

Data pipelines

Pandas

Job description

Bank of America seeks a seasoned quantitative researcher to design and implement volatility-driven strategies and risk analytics for institutional clients. You will build end-to-end modeling frameworks, back-testing pipelines, and risk analyses using Python within a collaborative, cross-functional environment.

The role emphasizes advanced timeseries modeling, ML/deep learning techniques, and strong communication to educate stakeholders on quantitative offerings and new strategies.