Quantitative Analyst – Quant Analyst Program

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

Millennium's Global Risk Management Department is responsible for identifying, measuring, monitoring, managing and reporting on the risks associated with Millennium's portfolios at the Firm-wide and Portfolio Manager levels, with a focus on the market, credit and liquidity risks the Firm faces in the course of its business. At the Portfolio Manager level, the team establishes and monitors trading parameters, risk guidelines and performance metrics across three regions and multiple product classes, and also monitors aggregations of risk up to the full Firm-wide level. Within Risk Management, the Quantitative Strategies team is a collaborative and entrepreneurial investment team that develops quantitative investment strategies across asset classes, including equities, fixed income, commodities, credit and FX, and across a broad set of instruments spanning futures, forwards, options, swaps and cash products. The team works across the full research lifecycle: idea generation, data sourcing, signal development, model implementation, backtesting, portfolio construction and live strategy refinement. The team is launching a Quant Analyst Program designed to develop early-career quants over 18–24 months into strong, cross-asset systematic researchers through formal technical training, asset class rotations, cross-functional exposure and supervised contribution to the quantitative strategies platform, with senior quant mentorship and quarterly development goals throughout.

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, 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 with attention to robustness, implementation, transaction costs, liquidity, and risk exposures, following the team's standards for reproducible, peer-reviewed research.
• 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, with scope increasing over the program.

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 such as pandas, NumPy, SciPy, Polars, scikit-learn, or similar tools; SQL experience and C++ are a plus.
• 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; prior internship or research exposure to finance is helpful but not required.
• Research discipline and the demonstrated ability to conduct independent, reproducible research, evidenced by academic projects, a thesis or dissertation, publications, or internships.
• Familiarity with derivatives, machine learning, large datasets, or time series analysis is helpful but not required.
• High intellectual curiosity, creativity, and proactive problem-solving.
• Strong written and verbal communication skills and the ability to work in a transparent, collaborative team.

Salary Range

Millennium offers a total compensation package which includes a base salary, discretionary performance bonus, and comprehensive benefits. The estimated base salary range for this position is $160,000 to $250,000, which is specific to New York and may change in the future. When finalizing an offer, we take into consideration an individual's experience level and the qualifications they bring to the role to formulate a competitive total compensation package.