About The Position

Investment Management Fintech Strategies (IMFS) is a global team headquartered in Malvern, Pennsylvania. We partner with investment teams to explore and apply new technologies that can improve investment performance, strengthen decision-making, and help capital markets work better for Vanguard’s investors. Our work spans advanced analytics and AI/ML, new data sources, market structure and liquidity research, and building scalable platforms and tools that move from experimentation into production.

Requirements

  • 5+ years leading or driving advanced data science work, including back-testing, simulation, and statistical modeling in complex problem spaces.
  • Master’s or PhD in machine learning, data science, financial engineering, computer science, or related quantitative discipline.
  • Strong end-to-end data science capability: problem framing → research design → modeling → validation → deployment partnership.
  • Proficiency in Python and common ML libraries; experience collaborating with data engineering and bringing models into production.
  • Demonstrated ability to apply AI/ML to solve complex technical problems through collaboration, creativity, and disciplined research.
  • Comfortable partnering with senior leaders—communicating tradeoffs, impact, and value in a clear, decision-oriented way.

Responsibilities

  • Own end-to-end research using large-scale historical data: form hypotheses, run analyses, develop models, and translate results into insights that can improve portfolio construction and trading decisions.
  • Identify and solve market-impact problems across microstructure, fund flows, and liquidity dynamics—surfacing risks and opportunities tied to execution quality and market impact.
  • Design and lead the evolution of core research tooling, including the back-testing framework and signal libraries, to enable repeatable, high-quality experimentation.
  • Apply AI/ML thoughtfully in financial markets, staying current on emerging techniques and evaluating what is practical, robust, and scalable in real-world market environments.
  • Raise the bar on engineering quality by mentoring quant strategists and data scientists on production-grade code, data pipelines, and research-to-production best practices.
  • Partner with technology to integrate models into production systems, monitor live performance, and iterate based on market feedback and measured outcomes.
  • Represent Vanguard externally by contributing to industry discussions and thought leadership in areas relevant to AI/ML, systematic research, trading, and market structure.
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