Quantitative Analyst – Quant Analyst Program
About The Position
Millennium’s Global Risk Management Department identifies, measures, monitors, manages, and reports on portfolio risks, including market, credit, and liquidity risk. Within that department, the Quantitative Strategies team develops quantitative investment strategies across asset classes and instruments, working through the full research lifecycle from idea generation and data sourcing to signal development, implementation, backtesting, portfolio construction, and live strategy refinement. The Quant Analyst Program is an 18–24 month development program intended to develop early-career quants into cross-asset systematic researchers. It combines formal technical training, rotations across asset classes, cross-functional exposure, supervised contributions to the quantitative strategies platform, senior quant mentorship, and quarterly development goals.
Requirements
- 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 and data libraries such as pandas, NumPy, SciPy, Polars, scikit-learn, or similar tools.
- Strong grounding in statistics, probability, optimization, and empirical modeling, with rigorous model evaluation and healthy skepticism around overfitting.
- Genuine interest in financial markets and systematic investing.
- Ability to conduct independent, reproducible research, evidenced by academic projects, a thesis or dissertation, publications, or internships.
- High intellectual curiosity, creativity, and proactive problem-solving.
- Strong written and verbal communication skills and ability to work in a transparent, collaborative team.
Nice To Haves
- SQL experience.
- C++ experience.
- Prior internship or research exposure to finance.
- Familiarity with derivatives, machine learning, large datasets, or time series analysis.
Responsibilities
- Complete formal training in backtesting methodology, signal design, portfolio construction, risk and volatility modeling, and transaction cost modeling.
- Rotate through research across equities, FX, rates, commodities, and options/volatility, learning market structure, common alpha sources, implementation constraints, and risk frameworks.
- Conduct original research and contribute signals and features across themes including equity risk premia, carry, momentum, value, flows, volatility, and dispersion.
- Build and improve shared research infrastructure, including data pipelines, backtesting tools, risk and volatility models, transaction cost models, and performance diagnostics.
- Analyze strategy performance for robustness, implementation, transaction costs, liquidity, and risk exposures, following standards for reproducible, peer-reviewed research.
- Gain exposure to trading, operations, compliance, technology, and risk to understand how ideas become investable strategies.
- Partner 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, with scope increasing over the program.
Benefits
- Comprehensive benefits
- Discretionary performance bonus
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
