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Senior Data Scientist — Investment Management Fintech Strategies (IMFS) at Vanguard
About the role
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.
Required skills
Data science
Machine learning
Statistical modeling
Quantitative research
Backtesting
Python
Market data analysis
Mentoring
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About Vanguard

Vanguard
PublicA client-owned investment company that offers low-cost mutual funds, ETFs, advice, and related services to institutional and individual investors, and financial professionals.
10,001+
Employees
Kelayres
Headquarters
Reviews
10 reviews
4.1
10 reviews
Work-life balance
3.8
Compensation
2.5
Culture
4.2
Career
3.2
Management
4.3
75%
Recommend to a friend
Pros
Supportive management and leadership
Great work-life balance and flexibility
Strong team collaboration and culture
Cons
Low or non-competitive compensation
Limited career advancement and promotions
Heavy workload and long hours
Salary Ranges
756 data points
Junior/L3
Senior/L5
Staff/L6
Senior
Junior/L3 · Data Scientist
0 reports
$142,083
total per year
Base
-
Stock
-
Bonus
-
$120,000
$164,000
Interview experience
3 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Interview process
1
Application Review
2
Online Assessment/Case Study
3
Phone Interview
4
Technical Interview
5
Final Round Interview
6
Offer
Common questions
Technical Knowledge
Behavioral/STAR
Past Experience
Case Study
Coding/Algorithm
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