2027 PhD Summer Intern – Portfolio Management, Quantitative Research Analyst
PIMCOAbout the role
PIMCO is a global leader in active fixed income. With our launch in 1971 in Newport Beach, California, PIMCO introduced investors to a total return approach to fixed income investing. In the 50+ years since, we have worked relentlessly to help millions of investors pursue their objectives – regardless of shifting marketing conditions. As active investors, our goal is not just to find opportunities, but to create them. To this end, we remain firmly committed to the pursuit of our mission: delivering superior investment returns, solutions, and service to our clients. Since 1971, our people have shaped our organization through a high-performance inclusive culture, in which we celebrate diverse thinking. We invest in our people and strive to imprint our CORE values of Collaboration, Openness, Responsibility and Excellence. We believe each of us is here to help others succeed and this has led to PIMCO being recognized as an innovator, industry thought leader and trusted advisor to our clients. 2027 PhD Summer Internship – Portfolio Management, Quantitative Research Analyst Internship positions are located at PIMCO’s Newport Beach, CA Headquarters
Eligibility Criteria
To apply, you must meet the following requirements
Be a Ph.D. candidate from a top program in quantitative fields such as Finance, Economics, Statistics, Computer Science, Operations Research, Physics, or Mathematics. Expected graduation from the Ph.D. program between Dec 2027 and June 2028 Have business proficiency in English. PM Analytics The PM Analytics team collaborates closely with Portfolio Management to provide quantitative inputs to PIMCO’s investment process. This includes developing models for alpha generation and risk management. Team members may specialize in specific markets (e.g., credit, rates, mortgages) or take on cross-market roles such as asset allocation, portfolio construction, or execution. Key responsibilities involve conducting econometric analyses of historical returns, bu
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