Senior Quantitative Data Scientist

Advanced Analytics solutions play a key role in supporting Vanguard's Investment Management strategies. In this role, you will be working as a Quant Research Scientist aligned to technology deployment that supports the growth of solutions directly influencing Vanguard's Investment Management strategies for our business teams. You will be part of a high-profile Applied R&D team enabling creative and impactful solutions across Active Equities, Fixed Income, Risk Management, Corporate Finance, and more. Our diverse research lab leads the application of deep learning, convex optimization, game theory, stochastic simulation, and more techniques for production solutions across all parts of Investment management. This opportunity is best aligned to individuals with experience in various parts of systematically designed research and engineering efforts. We are specifically looking for individuals with mathematical optimization and applied mathematics skill sets to complement the existing staff with this focus.

Responsibilities

• Significant experience in research settings regarding mathematical optimization and other modeling paradigms.
• Experience building machine learning architectures to address specific problem statements is nice to have.
• Comfortable with Quant standards such as Markowitz and Modern Portfolio Theory, mixed-integer optimization, Black-Litterman, factor models, etc.
• Proficient with python in development environments such as SageMaker, Databricks, etc.
• Experience creating evaluation frameworks with OOS, Sim, and back-test components and analyzing results.
• Experience with Investment Management related data and tasks is preferred.
• Participation or completion of the CFA or related financial knowledge is valuable.
• Ability to read & reproduce research papers in computational settings.
• Participation in systematic or quantitative workflows in Investment Management is a plus.

Qualifications

• Undergraduate degree in related STEM field(s) with Modeling work required.
• Graduate Degree or equivalent industrial experience in applied research or engineering workflows preferred.
• Strong coursework in mathematics, information theory, and other topics related to theoretical reasoning in modeling is necessary.
• Strong written and oral communication skills.

Special Factors

Vanguard is not offering visa sponsorship for this position. This position is hybrid and would require you to be in our London office three days per week.

Why Vanguard?

Vanguard is a different kind of investment company. It was founded in the United States in 1975 on a simple but revolutionary idea: that an investment company should manage its funds solely in the interests of its clients. This is a philosophy that has helped millions of people around the world to achieve their goals with low-cost, uncomplicated investments. It's what we stand for: value to investors.

Inclusion Statement

Vanguard's continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: "Do the right thing." We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard's core purpose through our values. When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard's core purpose: to take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.

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.