Lead / Senior AI/ML Data Scientist

Vanguard; Malvern (Chester County); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Vanguard is seeking a Senior Data Scientist for Investment Management Fintech Strategies (IMFS) in Malvern, PA. You will lead end-to-end research on large historical datasets to inform portfolio construction and trading decisions, while advancing modeling, back-testing, and production deployment practices.

The role calls for strong Python expertise, advanced degrees, and a track record of translating research into production.

Qualifications

• 5+ years leading or driving advanced data science work, including back-testing, simulation, and statistical modeling.
• 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.

Skills

Data science leadership

ML research & modeling

Python & ML libraries

Production deployment

Communication with leadership

Education

Master's or PhD in ML/DS/financial engineering

Tools

Python

Pandas/NumPy

Scikit-learn/MLlib

Job description

Senior Data Scientist - Investment Management Fintech Strategies (IMFS)

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.

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.

Qualifications

• 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.

Special Factors

• Sponsorship Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.