Quantitative Researcher Market Impact Modeling

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millenniums 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

Central Liquidity Strategies (CLS), within Execution Services, manages portfolios and products designed to optimize Millenniums trading and execution approach. The team provides internal liquidity solutions to Portfolio Managers on both a risk and agency basis, bringing together quantitative research, trading, and engineering to support these capabilities.

What You'll Do

Research, improve, and implement market-impact models across equities and other asset classes, drawing on current academic research and practical market experience
Estimate market impact using real-world data, addressing data biases, endogeneity, causal inference, and model robustness
Develop and enhance research, model-fitting, and analytics frameworks to support experimentation and model calibration
Partner with trading and engineering stakeholders to integrate models into the portfolio construction process
Communicate research findings, assumptions, and limitations clearly, translating business goals into quantitative research deliverables

What You Bring

A masters or PhD in Physics, Mathematics, Operations Research, Statistics, Finance, Economics, Econometrics, Financial Engineering, Econophysics, or a related discipline
Experience in quantitative research or quantitative trading, with a significant focus on market-impact research or market microstructure
Significant experience analyzing real-world datasets and estimating market impact in practical settings
Strong knowledge of relevant academic research and the challenges of data bias, endogeneity, causal inference, and robustness
Excellent analytical and quantitative skills
Proficiency in Python and kdb+/q
Strong communication and collaboration skills, with the ability to explain research outputs and limitations and align research with business objectives