Quant jobs / MSCI

Quantitative Researcher – Equity Factor Models

A research role in an equity investment research team that builds new analytics products from factor research. You combine financial theory with careful statistics.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Run equity factor research that links theory to empirical evidence
Turn research into inputs for new equity analytics products
Prepare research for publication and client-facing thought leadership
Present methods and findings to product, technology and sales colleagues

What they ask for

Required

Python
Econometrics
Applied statistics
Quantitative research design
AI-assisted development tools
Independent project delivery

Education: Master's or PhD in finance, physics, maths, statistics, operations research, economics or another quantitative discipline
Experience: Not stated
Languages and tools: Python
Markets: equities

How to prepare

Replicate a classic equity factor study (such as Fama-French) with careful data handling
Practise cross-sectional regressions, Fama-MacBeth and multiple-testing corrections
Write a short research note with clear tables and caveats
Review factor crowding and decay literature

What to study

The Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

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View the posting on MSCI’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with MSCI and doesn’t handle applications.