Quantitative Program Manager – Helios

Quantitative Program Manager – Helios 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 The Execution Services team supports trading across products and geographies, with a focus on execution quality, trading efficiency, and the tools that help portfolio managers make informed decisions. Within this group, Central Liquidity Strategies develops and operates trading capabilities that support internal liquidity solutions across the platform. The Helios team works at the intersection of engineering, data, and trading operations, with a strong focus on process reliability, production quality, and the systems that support research and model delivery. What You'll Do • Own project management for Helios, including ticket management, release coordination, cross-team dependencies, and status reporting to CLS stakeholders • Coordinate the release cadence across Helios, including release notes, sign-off tracking, and post-release verification • Test new features and model releases as an end user would before they reach internal users, identifying issues and usability gaps early • Collect, triage, and route incoming issues from users and downstream systems, acting as the primary liaison with the Support team • Monitor the daily health of production pipelines, model performance, and reconciliation reports, and investigate anomalies through basic diagnostic analysis • Take ownership of data correctness across reference data, model outputs, and live-versus-historical reconciliations • Drive improvements to runbooks, on-call procedures, and internal documentation to strengthen operational reliability • Use Python, AI, and other engineering tools to automate recurring work such as dashboards, health checks, release verification, triage workflows, and status reporting What You Bring • 6+ years of experience in a hybrid engineering, data analyst, and delivery role, ideally within quantitative finance, market data, or a similarly data-sensitive environment • Bachelor’s degree in a quantitative or technical discipline such as Computer Science, Mathematics, Physics, Engineering, or a related field • Hands-on experience with Python or kdb+, ideally both, with the ability to independently analyze data, run sanity checks or regressions, visualize results, and reconcile data sources • Strong automation mindset, with the ability to use code and AI to reduce manual work and improve team efficiency • Deep familiarity with project management and issue-tracking tools, release management, and structured incident and issue workflows • Strong attention to detail and a clear commitment to data correctness, process discipline, and operational quality • Excellent written and verbal communication skills, with the ability to produce clear release notes, runbooks, and status updates and to drive teams toward decisions • Prior experience with equities trading systems, market data pipelines, model validation processes, or on-call and incident management practices is a plus