Options Execution Researcher

Responsibilities

• Build and maintain options pricing and valuation models calibrated to digital asset volatility markets
• Develop execution algorithms for options and structured derivatives, including entry/exit timing, hedging logic, and delta management
• Research volatility dynamics across crypto markets, focusing on term structure, skew, and cross-asset relationships
• Analyse microstructure on options venues to improve fill quality and reduce execution costs
• Construct and maintain rigorous backtests for options strategies, accounting for path dependency, margin, and transaction costs
• Collaborate with engineers to deploy execution models into live production infrastructure
• Monitor live strategy Greeks and P&L attribution in real time to iterate on models

Requirements

• Strong quantitative background in mathematics, physics, financial engineering, or computer science
• Deep understanding of options pricing theory, including Black-Scholes and stochastic volatility models (Heston, SABR, local vol)
• Hands-on experience building execution models or systematic options strategies at a trading firm, hedge fund, or structured products desk
• Familiarity with crypto derivatives markets (e.g., Deribit, OKX, Bybit)
• Strong proficiency in Python
• Rigorous approach to backtesting with experience managing pitfalls like slippage estimation and model overfitting

Preferred Qualifications

• Knowledge of C++ for latency-sensitive execution work
• For senior candidates: a live, attributable track record in options market making, volatility arbitrage, or systematic derivatives trading

About the Company

AlgoQuant Asset Management is a multi-strategy digital asset manager allocating capital across 25+ internal and external quantitative trading pods. Founded in 2018, we have evolved into an institutional platform combining trading edge with strong governance and advanced technology, serving family offices and institutional investors globally.