Quantitative Equity Research Analyst

Overview

As a Quantitative Equity Research Analyst at Fidelity, you will develop multi-factor models and run empirical analyses to support alpha generation, risk management, and portfolio construction alongside fundamental PMs. You’ll explore large datasets and new alpha sources to inform investment decisions and assist with product development and client communications. You join a research-driven Equity Quantitative team within QRI, contributing to the agenda and publishing insights internally. You will apply advanced analytics and ML techniques to translate model outputs into actionable investment ideas. This role offers meaningful impact through shaping quantitative investment strategies at scale.

Responsibilities

• Build and test quantitative factors and models to enhance the investment process for fundamental PMs
• Evaluate large structured and alternative datasets to identify differentiated alpha sources
• Provide tailored risk analyses, explore portfolio construction and optimization techniques, and perform performance attribution
• Support new product development, fund pitches, and client communications
• Contribute to the team research agenda and own research projects, including internal publication and dissemination

Key requirements

• 7+ years of experience in quantitative equity research
• Experience building multi-factor quantitative models using linear and non-linear (ML/GenAI) approaches
• Deep understanding of equity risk models, factor/covariance concepts, and translating statistics into investor-friendly insights
• Proficiency in programming languages and statistical software (Python, R, SQL)
• Experience with portfolio construction and optimization techniques
• Working knowledge of extracting insights from unstructured data using large language models
• Experience with financial databases (e.g., Compustat, Worldscope, IBES) and tools (FactSet, Bloomberg, Barra)
• Master’s degree in quantitative finance, financial mathematics, business administration, computer science, engineering, or the physical sciences
• Strong independent thinking, economic intuition, and presentation/communication skills

• independent thinking
• strong presentation and communication
• economic intuition
• multi-factor model development
• linear and non-linear modeling
• machine learning / GenAI applications

…