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Quantitative Trading & Research – Equity Derivatives Flow - Vice President
mid · Data Science & Analytics
The Quantitative Trading & Research Team (QTR) Equity Derivatives group seeks a junior to mid-level quantitative researcher to focus on flow products. The role centers on driving and implementing analytics, optimization, and modeling across volatility trading, encompassing volatility surface calibration, client analytics, and pre-trade/post-trade analysis and hedging optimization.
Job Summary:
As a Vice President for the Quantitative Trading & Research Team, you will leverage data and advanced quantitative techniques, including machine learning, to build end-to-end solutions that directly support the business.
Job Responsibilities:
- Partner with the Equity Derivatives Flow trading desk to build analytics and develop, enhance, and maintain pricing and risk models for flow products.
- Lead research and implementation of volatility trading analytics, with a focus on volatility surface calibration and modeling.
- Design and deliver client analytics tools, including pre-trade and post-trade analysis and hedging optimization frameworks.
- Take an active role in shaping a data-driven ecosystem for trading and risk management.
- Own the full project lifecycle — from ideation and prototyping to production deployment — developing analytics to manage client flow and risk inventory, supporting daily operations, and monitoring performance.
- Work closely with traders to translate quantitative research into clear, actionable insights and solutions.
Required Qualifications:
- Advanced degree (Master's or Ph.D.) in a quantitative discipline (Mathematics, Physics, Engineering, Computer Science, Financial Engineering, or related field) from a top-tier university.
- 1–3 years of experience in equity modeling, with a preference for equity derivatives.
- Strong foundation in stochastic calculus, probability theory, and numerical methods.
- Deep knowledge of option theory and equity derivatives products and markets.
- Proficiency in Python, C++, and relevant numerical computing packages.
- Demonstrated experience with quantitative research techniques, data analysis, and machine learning.
- Strong communication skills with the ability to engage effectively with trading and deliver production-ready solutions.
Preferred Skills:
- Experience analyzing market data and applying insights to derivatives trading strategies.
- Familiarity with risk management frameworks and relevant regulatory requirements.
- Prior exposure to a front-office quantitative research or trading environment.
- Proven ability to embed LLM-driven tools into quantitative research pipelines — whether for automating analysis, accelerating model development, or extracting insights from unstructured financial data.
- Self-motivated and intellectually independent, with a track record of identifying research opportunities, taking ownership of open-ended problems, and delivering results with minimal oversight.
- Curious and rigorous analytical thinker who challenges conventional assumptions, synthesizes ideas across domains, and translates original research into practical, high-impact trading tools.