Fixed Income – Quantitative Investment Analyst – Portfolio Construction

Do you excel in quantitative portfolio optimization for bond funds? Have you consistently helped fixed-income fund managers create more efficient portfolios? Join T. Rowe Price—this role is for you!

Role Summary

The Quantitative Investment Analyst is an investment role within the Fixed Income division at T. Rowe Price. The role resides within the Fixed Income Quantitative Investments and Research (FI Quant) group, as part of the Portfolio Research Group. The Portfolio Research Group seeks to enhance portfolio risk-adjusted returns by applying quantitative methods to: (a) advise portfolio managers on position sizing and optimal combination of positions in portfolios; (b) advise portfolio managers on risks not immediately covered by standard models; (c) capitalize on long-term market inefficiencies and risk premia as well as capture value from shorter-term dislocations.

The team requires an experienced quantitative researcher to conduct analysis in applied portfolio construction. A successful candidate will frequently interact with Fixed Income portfolio managers and senior Fixed Income leadership to advocate for implementation of relevant ideas and methods in fixed income portfolios.

Responsibilities

• Conduct quantitative research applied to US fixed income portfolios, involving sizing and combination of sectors, strategies and alpha signals, including off-benchmark segments
• Integrate solid risk-awareness in portfolio construction models, accounting for risk in normal and stressed market environments
• Proactively advocate for enhancing portfolio performance by applying appropriate quantitative methodologies and effectively collaborate with portfolio managers towards this goal
• Work with Technology partners to productionize models

Qualifications

Required:

• Degree in quantitative discipline. Master’s or higher preferred
• 7+ years of investing experience
• Experience and expertise in fixed income markets, securities, and derivatives instruments, especially instruments that involve credit risk.
• Understanding of quantitative portfolio construction and optimization techniques
• Proficiency with R or Python programming language
• Ability and willingness to leverage AI tools available in the company to boost efficiency is highly valued
• Familiarity with risk forecast models
• Self-motivated, independent, detail oriented and intellectually curious
• Strong communication skills, with ability to influence others.  Creative problem solver

Preferred:

• CFA designation
• Experience with US Securitized products, especially Mortgage Backed Securities (Agency and Non-Agency)

FINRA Requirements

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

Work Flexibility

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