Quantitative Trading & Research - Alpha Quant - Vice President

As a QTR member, you will drive innovation across the vol trading ecosystem by applying advanced data analytics, statistical modeling, and machine learning.

Join our global team and leverage your skills to shape the future of financial markets.

We offer comprehensive training and growth opportunities to enhance your skills and advance your career.

Our diverse team supports a wide range of business functions, providing a unique environment for professional development.

We are committed to accommodating diverse needs and fostering an inclusive workplace.

Job Summary

As an Alpha Quant on the Quantitative Trading & Research (QTR) Equity Derivatives team, you will focus on end-to-end alpha research and strategy deployment across equity options and volatility markets.

You will help drive the alpha research agenda for Systematic Derivatives, using data analytics and software engineering to deliver research-to-production strategies.

Your role will involve feature engineering from diverse data sources, building robust alpha calibration, attribution, and monitoring frameworks, partnering closely with trading, and implementing systematic strategies with strong attention to execution, hedging, and risk.

Job Responsibilities


* Work closely with trading to build end-to-end design and implementation of daily and intraday signal research and deployment infrastructure, with special focus on equity derivatives / Systematic derivatives.


* Contribute from idea generation to production implementation: perform research, design prototypes, implement alpha signals and systematic strategies; support daily usage, monitor performance, and iterate based on live feedback.


* Research and model equity options and volatility dynamics (e.g., surface arbitrage, term structure, skew, dispersion, event risk, RV) and translate insights into deployable systematic strategies.


* Develop and maintain robust backtesting, attribution, and regime analysis frameworks tailored to derivatives PnL drivers.


* Build models that integrate fundamental, quantitative, and microstructure features to support risk internalization and/or risk warehousing, using statistics, machine learning, or heuristics as appropriate.


* Partner with the business on alpha capture, risk recycling, hedging design, and position/risk management for derivatives strategies (including Greeks and scenarios).


* Collaborate broadly with QTR teams across regions to build reusable research libraries, tooling, and standardized workflows for experimentation, deployment, and monitoring.


* (Plus) Leverage AI/ML and modern AI tooling to accelerate research and improve developer productivity, with an understanding of AI product ionization (model governance, evaluation, monitoring, and safe professional use of AI agents).

Required Qualifications, Capabilities, and Skills


* You have a strong quantitative background, as well as practical problem-solving skills.


* You have direct wor...