Quantitative Researcher

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Meet the Team

The Volatility Alpha Development team is the core quantitative and strategy group supporting Millennium’s global volatility business. The team builds and maintains systematic options datasets, back testing infrastructure, event-volatility models, and live systematic volatility-fitting frameworks that support portfolio managers across global volatility strategies.

What You'll Do

• Conduct quantitative research on market volatility, including volatility-surface fitting, systematic options P&L dataset generation, event-volatility analysis, alternative-data research, AI-based hypothesis testing, and backtesting-platform development.
• Research global systematic options markets, including single-stock versus index spreads and bespoke ETFs, to develop datasets and prototype strategies that support alpha portfolio manager investment processes.
• Combine financial intuition with statistical learning techniques to develop predictive models for use in the investment process.
• Partner with senior portfolio managers to integrate Volatility Alpha Development datasets into investment strategies and risk-management workflows.
• Contribute to prototype alpha-strategy development across the Volatility Alpha Development platform.

What You Bring

• Master’s degree or PhD in physics, mathematics, statistics, engineering, operations research, or a related STEM discipline.
• At least three years of experience in investment management or a quantitative research environment.
• Strong programming skills in Python, R, MATLAB, or C++.
• Deep knowledge of financial markets, with particular expertise in options and derivatives.
• Experience applying machine learning, statistical modeling, and data-visualization techniques.
• Excellent analytical, problem-solving, and communication skills.