Description
Millennium's Global Risk Management Department is responsible for identifying, measuring, monitoring, managing and reporting on the risks associated with Millennium's portfolios. The Quantitative Strategies team is a collaborative and entrepreneurial investment team that develops quantitative investment strategies across asset classes. The team is launching a Quant Analyst Program designed to develop early-career quants over 18–24 months into strong, cross-asset systematic researchers.
What You'll Do
- Complete a structured 18–24 month development program combining formal technical training in backtesting methodology, signal design, portfolio construction, risk and volatility modeling, and transaction cost modeling.
- Rotate through asset class research across equities, FX, rates, commodities, and options/volatility, learning market structure, common alpha sources, implementation constraints, and risk frameworks in each.
- Conduct original research and contribute new signals and features across quant themes.
- Build and improve shared research infrastructure, including data pipelines, backtesting tools, risk and volatility models, transaction cost models, and performance diagnostics.
- Analyze strategy performance with attention to robustness, implementation, transaction costs, liquidity, and risk exposures.
- Gain hands-on exposure to trading, operations, compliance, technology, and risk to understand how ideas become investable strategies.
- Partner closely with senior quants, portfolio managers, and technologists to move ideas from research into shadow and production.
- Present research in regular team seminars and take ownership of an independent research project.
What You Bring
- Advanced undergraduate, Master’s, or PhD degree (completed or expected) in a quantitative field such as mathematics, statistics, computer science, physics, engineering, or economics/econometrics.
- Strong Python skills, including experience with common scientific/data libraries.
- Strong grounding in statistics, probability, optimization, and empirical modeling.
- Genuine interest in financial markets and systematic investing.
- Research discipline and the demonstrated ability to conduct independent, reproducible research.
- High intellectual curiosity, creativity, and proactive problem-solving.
- Strong written and verbal communication skills and the ability to work in a transparent, collaborative team.