Quantitative Researcher

Location: New York

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 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.

What You’ll DoConduct original research and develop systematic investment strategies across all asset classes, including equities, rates, commodities, credit, and FX.Generate and test new research ideas using financial intuition, statistical learning, and large, diverse datasets.

Build and improve research infrastructure, including data pipelines, signal analytics, backtesting tools, and portfolio analytics.

Analyze strategy performance with attention to robustness, implementation, transaction costs, liquidity, and risk exposures.

Research opportunities across futures, forwards, options, swaps, and cash instruments, including relative value, directional, and cross-asset themes.

Partner closely with portfolio managers, researchers, and technologists to move ideas from research into production.

Monitor live strategies and refine models based on empirical results and changing market behavior.

What You Bring Advanced degree in an applied quantitative field such as statistics, econometrics, computer science, engineering, operations research, financial engineering, applied mathematics, or data science;
PhD preferred but not required, and exceptional candidates with a Bachelor’s or Master’s degree or equivalent industry experience will also be considered

Excellent Python skills, including experience with common scientific/data libraries such as pandas, Num Py, Sci Py, Polars, scikit-learn, or similar tools, and the ability to build clean, scalable research code.

Strong grounding in statistics, probability, optimization, and empirical modeling, with rigorous model evaluation and healthy skepticism around overfitting.

Experience working with large financial datasets, market data, and reproducible research workflows.

Ability to build clean, scalable research code and evaluate models rigorously.

Experience in quantitative research, systematic investing, hedge funds, asset management, or related research environments, with a preference for training rooted…