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
Core to the health and growth of our business, Millenniums Information Technology organization builds flexible, scalable platforms and advanced proprietary systems that support the firms active, multi-manager model. Within this environment, the Systematic Data group brings together content specialists, data scientists, engineers, and quantitative developers focused on discovering, maintaining, and analyzing sources of alpha for portfolio managers. The teams data platform powers the firms systematic portfolio engines and supports research across data, statistics, technology, and financial markets.

What You'll Do
Design, develop, and enhance the firms central backtesting platform
Explore and analyze a wide range of datasets to assess their characteristics, quality, and potential investment value
Build and maintain tools to evaluate, monitor, and improve data quality and integrity across diverse data sources
Create curated data products by combining and enriching multiple datasets to deliver research-ready content to portfolio managers
Partner with portfolio managers and quantitative analysts to understand use cases and support research workflows
Collaborate with a global team of quantitative developers, data scientists, and content specialists across regions

What You Bring

23 years of experience as a quantitative developer, software engineer, or data engineer

Bachelors or Masters degree in Computer Science, Electrical Engineering, or a related quantitative discipline from a top-tier institution

Strong programming and software development skills, with hands-on expertise in Python

Familiarity with data pipeline engineering and ETL for large datasets; experience with scheduling tools such as Airflow is a plus

Strong SQL and database experience

Solid understanding of the software development lifecycle, including Linux, Git, and CI/CD

Excellent communication skills, with the ability to work directly with portfolio managers and quantitative analysts

Knowledge of financial markets, backtesting, risk models, performance attribution, or applied statistical techniques is a plus