Volatility Portfolio Manager
Manage a standalone volatility portfolio consisting of index vol, delta, and single name exposures. Analyze and model U.S. listed equity and index option markets to identify relative value and volatility arbitrage opportunities. Design and implement systematic and discretionary trading strategies across listed options and related derivatives. Perform ongoing risk analysis, scenario testing, and exposure monitoring to maintain balanced volatility and directional risk. Optimize capital utilization and risk-adjusted returns within the firm's multi-strategy framework. Develop and refine volatility forecasting and correlation models using market and historical data. Research and monitor structural market dynamics, including dealer positioning, ETF hedging flows, and single-name dispersion trends. Execute trades efficiently across U.S. exchanges while maintaining discipline around execution quality, transaction costs, and market impact. Integrate proprietary analytics, data pipelines, and execution systems to enhance signal generation and portfolio construction. Manage daily P&L attribution, variance decomposition, and exposure reporting with precision and transparency. Collaborate with quantitative researchers and developers to improve modeling frameworks, data ingestion, and simulation tools. Continuously evaluate portfolio performance, adapt strategies to changing market regimes, and iterate on risk frameworks. Maintain strong compliance with firm policies, exchange rules, and U.S. regulatory requirements. Communicate trading rationale, performance insights, and market observations to senior management and risk oversight teams. Contribute to the enhancement of the firm's equity volatility platform through research, collaboration, and innovation. Requirements: Masters degree (US or foreign equivalent) in Finance, Computational Finance, or a related field and three (3) years of experience in the position offered or in a related role. All of the required experience must have included experience with: quantitative modeling of U.S. equity and index volatility surfaces, skew, and term structures; utilizing knowledge of options pricing, Greeks decomposition, and volatility risk management across listed products (i.e. financial instruments that trade on regulated exchanges); Python or C++; building or using backtesting and risk systems; utilizing knowledge of U.S. listed options market microstructure, including liquidity dynamics, open interest, and flow behavior; designing and managing dispersion, correlation, and relative value strategies across single names and indices; volatility forecasting, realized vs. implied analysis, and correlation estimation; gamma/vega management, forward variance modeling, and volatility-of-volatility dynamics; high-performance data processing, low-latency execution, and automated trading infrastructure; integrating data-driven or statistical learning techniques into trading and risk frameworks; and utilizing knowledge of equity index composition effects, corporate actions, and event-driven volatility behavior. This role entails hybrid work, with time split between working in our New York, NY office and flexibility to telecommute from another U.S. location. To apply: E-mail resume to: hr@walleyecapital.com.
Manage a standalone volatility portfolio consisting of index vol, delta, and single name exposures. Analyze and model U.S. listed equity and index option markets to identify relative value and volatility arbitrage opportunities. Design and implement systematic and discretionary trading strategies across listed options and related derivatives. Perform ongoing risk analysis, scenario testing, and exposure monitoring to maintain balanced volatility and directional risk. Optimize capital utilization and risk-adjusted returns within the firm's multi-strategy framework. Develop and refine volatility forecasting and correlation models using market and historical data. Research and monitor structural market dynamics, including dealer positioning, ETF hedging flows, and single-name dispersion trends. Execute trades efficiently across U.S. exchanges while maintaining discipline around execution quality, transaction costs, and market impact. Integrate proprietary analytics, data pipelines, and execution systems to enhance signal generation and portfolio construction. Manage daily P&L attribution, variance decomposition, and exposure reporting with precision and transparency. Collaborate with quantitative researchers and developers to improve modeling frameworks, data ingestion, and simulation tools. Continuously evaluate portfolio performance, adapt strategies to changing market regimes, and iterate on risk frameworks. Maintain strong compliance with firm policies, exchange rules, and U.S. regulatory requirements. Communicate trading rationale, performance insights, and market observations to senior management and risk oversight teams. Contribute to the enhancement of the firm's equity volatility platform through research, collaboration, and innovation. Requirements: Masters degree (US or foreign equivalent) in Finance, Computational Finance, or a related field and three (3) years of experience in the position offered or in a related role. All of the required experience must have included experience with: quantitative modeling of U.S. equity and index volatility surfaces, skew, and term structures; utilizing knowledge of options pricing, Greeks decomposition, and volatility risk management across listed products (i.e. financial instruments that trade on regulated exchanges); Python or C++; building or using backtesting and risk systems; utilizing knowledge of U.S. listed options market microstructure, including liquidity dynamics, open interest, and flow behavior; designing and managing dispersion, correlation, and relative value strategies across single names and indices; volatility forecasting, realized vs. implied analysis, and correlation estimation; gamma/vega management, forward variance modeling, and volatility-of-volatility dynamics; high-performance data processing, low-latency execution, and automated trading infrastructure; integrating data-driven or statistical learning techniques into trading and risk frameworks; and utilizing knowledge of equity index composition effects, corporate actions, and event-driven volatility behavior. This role entails hybrid work, with time split between working in our New York, NY office and flexibility to telecommute from another U.S. location. To apply: E-mail resume to: hr@walleyecapital.com.