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Quantitative Developer

Goldman Lloyds

Quantitative Developer – Equity Derivatives | Options | Leading Investment Firm | New York | Hybrid We are working confidentially with a leading investment firm to identify a Quantitative Developer for a hybrid quantitative development and research role within their equity derivatives options function. This is a rare seat sitting at the intersection of rigorous quantitative research and production engineering — contributing directly to the buildout of the firm's options analytics and strategy infrastructure. The Role You will operate across both research and development — contributing to the design and implementation of options pricing models, volatility frameworks, and strategy analytics while engineering the production systems that bring that research to life. The firm needs someone equally comfortable deriving a model and building the system that runs it in production. What You'll Be Doing Contributing to quantitative research across options pricing, volatility surface modeling, and derivatives strategy development Building and maintaining production-grade analytics infrastructure supporting equity derivatives options strategies Developing and backtesting options strategies — owning the framework design, not just running existing tools Productionising research models — translating quant research into robust, scalable production systems Building data pipelines and analytics services for options market data, Greeks, and strategy performance attribution Partnering directly with portfolio managers and quant researchers to deliver analytical tools that feed directly into investment decisions What We Are Looking For Deep understanding of equity derivatives — options pricing, Greeks, volatility surfaces, and derivatives strategy mechanics Quantitative research capability — comfortable deriving, implementing, and validating options models Experience building production analytics systems — not just research notebooks Backtesting framework experience — ideally built from scratch rather than configured from existing platforms Strong mathematical foundations — stochastic calculus, probability, and numerical methods applied to derivatives pricing Prior experience in a hybrid quant development and research capacity at a hedge fund, prop trading firm, or investment bank Beneficial C++ experience alongside Python for performance-critical components Experience with volatility modeling — local vol, stochastic vol, or SABR frameworks Options market microstructure knowledge Experience productionising options pricing or strategy models in a live trading environment Location: New York | Hybrid Compensation: Base + Bonus (Advertised is base salary only) #J-18808-Ljbffr

Vacancy posted 3 days ago
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