Quantitative Investment Analyst – Multi-Asset

About the Team

T. Rowe Price’s Multi-Asset Division collectively manages $550bn+ across a growing range of global retirement mandates and provides a collaborative, outcome-oriented environment for quantitative researchers from diverse academic and professional backgrounds.

The Quantitative Investment Analyst role in the Multi-Asset Division is intended for an experienced, highly quantitatively skilled candidate who will join the Lifecycle Research team responsible for setting the strategic asset allocation of target date strategies and for developing personalized retirement investment solutions. Researchers on the team build analytical frameworks and conduct rigorous quantitative studies related to various aspects of retirement investing.

Main areas of focus span individual investor behavior, target date glide path construction and customization, personalized financial advice, household finance, and design of pooled and personalized retirement income solutions. In addition to deep, topic-specific research, the role requires active contribution to the team’s analytical infrastructure. Responsibilities include reviewing and updating quantitative models, curating core datasets, and partnering closely with quantitative developers to implement scalable, production-quality code.

The research environment at T. Rowe Price is highly interactive and places a strong emphasis on integrity, collaboration, and intellectual agility. Successful candidates demonstrate pragmatism, comfort with ambiguity, and a constructive approach to feedback and change. We seek individuals with a development mindset and a genuine interest in building comprehensive, robust analytical systems that shape investment outcomes for millions of retirement savers worldwide.

Prior financial industry experience is not required.

• Execute all stages of quantitative research, from project design to communicating results to the key stakeholders internally and externally
• Extend and maintain the team’s analytical and reporting infrastructure; this encompasses stewardship of core datasets, statistical models, and shared codebases
• Disseminate research findings: participate in industry conferences and webinars, write white papers, and publish in peer-reviewed journals

• Graduate degree in a STEM field
• Strong foundation in applied data science (e.g., experimental research in natural sciences, statistics, finance, or econometrics)
• Demonstrated programming proficiency, including developing and extending object-oriented, version-controlled code in MATLAB, Python, or Java
• Collaborative working style: willingness to listen, penchant for sharing knowledge, and responsiveness to business needs
• Ability to clearly convey complex analytical concepts and results to audiences with varying levels of technical expertise

• Ph.D. in a STEM field
• Expertise in operations research, optimization, and stochastic modeling

FINRA licenses are not required and will not be supported for this role.

This role is eligible for hybrid work, with up to one day per week from home.