Quantitative Investment Analyst: Multi-Asset Research – Macro Focus
The Analyst will conduct applied, investment-oriented quantitative analysis to support the investment activities of a group that collectively manages $250bn across a growing range of multi-asset mandates globally. The position resides in a dedicated Quantitative Multi-Asset Research Group at T Rowe Price, which provides a collaborative, solution oriented environment for quantitative researchers from a variety of backgrounds. The highly interactive and thorough investment process at T. Rowe Price leads us to put a premium on intellectual agility and honesty, tolerance for ambiguity, a collaborative demeanor, a high degree of pragmatism, and a constructive attitude towards change.
Specifically, this position would contribute to our asset class level factor investing program, with a special focus on the macro drivers of returns within and across asset classes. These new strategies would form a suite of overlays and signals for both discretionary and systematic strategies, and they would be employed either as an enhancement to other multi asset solutions or on a standalone basis. Some examples of areas that this individual would tackle include:
- Reviewing academic and practitioner research related to the macro drivers of returns, as well as replicating key results
- Advising, curating, and executing collaborative research projects aimed at assessing and harvesting macro-based return enhancements, including the need to manage a multi-person research agenda that involves other researchers and stakeholders
- Contributing to the broader cross-asset macro investment process by helping to identity the correct signals and relationships that senior investors in the firm should rely on
- Collaborating on, or selectively leading, other multi-asset research or systematic investing initiatives
- 3-5 years of relevant investment experience
- A graduate degree in a quantitative discipline, either in economics or (quantitative) finance, or in the natural sciences or engineering.
- A solid practical background in macroeconomics
- A strong foundation in applied empirical analysis (experimental work in natural sciences, statistics, econometrics, data science/machine learning)
- Strong programming skills and prior experience in working on collaborative programming efforts
- Some prior experience in capital markets and investment topics, either through work experience or educational background
- The ability to work effectively in a thoughtful, collaborative team environment
- Strong communication skills, being able to interface effectively with bright quantitative colleagues as well as non-technical audiences
The ideal candidate would additionally bring some of the following:
- 5-9 years of prior investing experience
- A Ph.D. in one of the disciplines listed above
- Prior experience in systematic, multi-asset risk or style premium investing
- Advanced proficiency in R, SQL and Git version control. Python and Matlab are a plus.
- CFA certification preferred but not required