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
Core to the health and growth of our business, Millennium’s Information Technology organization builds flexible, scalable platforms and advanced proprietary systems that support the firm’s 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 team’s data platform powers the firm’s systematic portfolio engines and supports research across data, statistics, technology, and financial markets.
What You'll Do
• Design, develop, and enhance the firm’s 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
• 2–3 years of experience as a quantitative developer, software engineer, or data engineer
• Bachelor’s or Master’s 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