Optimization Research Scientist

Vanguard; Malvern (Chester County); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Vanguard in Malvern, PA seeks an experienced researcher to join a high-profile Applied R&D team focused on optimization, ML, and quantitative methods in investment management. You will develop rigorous, data-driven solutions at the intersection of mathematics and finance.

Collaboration with research, engineering, and investment partners is essential as you translate complex questions into actionable models and decision-ready insights for portfolio strategies.

Qualifications

• Experience in applied research and quantitative modeling with independence to drive ambiguous research.
• Ability to translate questions into optimization or analytical approaches for investment contexts.
• Strong background in machine learning and deep learning is a plus.

Responsibilities

• Partner with senior stakeholders to uncover high-value opportunities and refine hypotheses.
• Formulate investment challenges as optimization problems with objectives and constraints.
• Build quantitative frameworks to support decision-making in real-world investment settings.
• Work with noisy, evolving data to create usable research datasets and document assumptions.
• Design robust evaluation approaches including backtesting and sensitivity analysis.
• Iterate with researchers, data scientists, and engineering partners toward scalable solutions.
• Communicate findings and recommendations clearly to business leaders.

Skills

Applied research

Quantitative modeling

Optimization

Machine learning

Python

Tools

SageMaker

Databricks

Optimization libraries

Job description

You will be part of a high-profile Applied R&D team focused on building creative and impactful solutions in investment management and finance. This multinational research and innovation lab supports the research, development, and deployment of advanced optimization, machine learning and quantitative methods, including deep learning, convex optimization, and stochastic simulation, across several parts of the investment management process. This opportunity is best suited for individuals with strong applied research experience who are excited to work at the intersection of quantitative modeling, mathematical modeling, machine learning, and investment decision-making. We are specifically looking for individuals with hands-on deep learning experience, strong quantitative intuition, and the ability to contribute rigorous, systematic solutions in collaboration with research, engineering, and investment partners.

Core Responsibilities

• Partner directly with senior business and investment stakeholders to uncover high-value opportunities, develop + iteratively refine hypotheses, and translate ambiguous questions into structured research problems.
• Formulate complex business and investment challenges as optimization problems, defining objectives, constraints, tradeoffs, decision variables, and measurable success criteria.
• Build and evaluate quantitative, statistical, machine learning, simulation, and optimization frameworks that support practical decision-making in real-world investment settings.
• Work with incomplete, noisy, fragmented, or evolving data to create usable research datasets, document assumptions, and assess the implications of data limitations.
• Design rigorous evaluation approaches, including out-of-sample testing, simulation, backtesting, sensitivity analysis, robustness testing, and constraint validation.
• Iterate closely with stakeholders, researchers, data scientists, and engineering partners to refine hypotheses, improve frameworks, and move promising research toward scalable implementation.
• Communicate findings, tradeoffs, assumptions, and recommendations clearly to business leaders, with a focus on decision impact and actionable next steps.

Qualifications

• Experience in applied research, quantitative modeling, optimization, and machine learning, with the ability to independently drive ambiguous research efforts from problem discovery through recommendation.
• Strong ability to partner directly with senior business stakeholders to uncover high-value opportunities, develop hypotheses, and translate loosely defined questions into rigorous analytical or optimization approaches.
• Experience formulating complex business or investment problems in terms of objectives, constraints, tradeoffs, decision variables, and measurable outcomes.
• Strong experience building optimization models to support decision-making in real-world settings, experience with statistical, machine learning, and deep learning is a plus.
• Comfort working with incomplete, noisy, fragmented, or evolving data, including the ability to make pragmatic assumptions, document limitations, and keep research moving despite imperfect inputs.
• Experience designing and interpreting evaluation frameworks using out-of-sample testing, simulation, backtesting, sensitivity analysis, or robustness analysis.
• Proficiency in Python and comfort working in development environments such as SageMaker, Databricks, or similar platforms; familiarity with optimization libraries, solvers, or computational decision frameworks is valuable.
• Experience with quantitative finance, systematic workflows, or investment management problems is preferred; participation in the CFA program or related financial education is valuable.

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.