Equity Derivatives Quant Researcher

Quantitative Researcher — Equity Derivatives | Event-Driven | New York / Miami Our client is a seasoned equity derivatives Portfolio Manager with twenty years of experience — including deep roots on both sides of the market — who has built a high-performing team within a leading global multi-strategy platform. The team is growing, with a deliberate focus on expanding its Miami presence. What Makes This Role Different The team's edge comes from understanding how specific corporate and market events create predictable, tradeable patterns in equity derivatives markets — and they are looking for a researcher who can help find, quantify, and systematize that edge. The research that matters here is idiosyncratic and event-specific. Strong mathematical foundations are essential — paired with deep quantitative rigor, professional curiosity to explore risk, and the discipline to focus. What You Will Work On The work centers on understanding how equity derivatives markets behave around corporate events — IPOs, secondary offerings, block trades, index rebalancing, earnings announcements, M&A; — and building systematic research frameworks that translate those insights into tradeable signals:• Vol crush and expansion patterns around event resolution• Implied volatility jump risk and earnings vol reset dynamics• Dealer gamma positioning and delta hedging flows around corporate events• Index rebalancing mechanics and passive flow impact on vol surfaces• Secondary offering and block trade price pressure and post-deal recovery• Feature engineering from options market data — skew, term structure, vol of vol, open interest• Production-grade backtesting frameworks and signal libraries• Systematizing discretionary pattern recognition at the intersection of equity derivatives and corporate events What You Bring • Graduate degree in mathematics, statistics, computer science, computational finance, physics, or engineering• 3+ years of quantitative research experience in equity derivatives markets• Fluency in Python — KDB/Q, C++, or Java a strong plus; familiarity with JAX, Option Metrics, Cboe Live Vol, CVXPY, Arctic, Zipline, or Nautilus Trader a differentiator• The curiosity to explore risk and the discipline to focus• Candidates with advanced degrees in seismology, geophysics, signal processing, turbulence modeling, inverse problems, or econophysics who have developed an interest in financial markets are encouraged to apply