Quant jobs / MSCI

Quantitative Researcher – Model Scaling

A research-platform role in the team supporting MSCI's factor and risk model research. You build AI-assisted tooling and governance pipelines that carry models from specification to production.

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.

Build research infrastructure that speeds up model development, validation and reporting
Create automated testing and governance pipelines for factor and risk models
Write production code to deliver and maintain existing models
Present platform changes to researchers, engineers and data teams

What they ask for

Required

Python software engineering
AI-assisted development tools
Large-scale data infrastructure
Econometrics
Applied statistics
Independent project delivery

Preferred

Finance or risk modelling knowledge

Education: MS or PhD in finance, statistics, computer science, engineering or another quantitative field
Experience: Not specified; independent delivery from design to production expected
Languages and tools: Python

How to prepare

Build a factor model pipeline with automated tests and reproducible runs
Study multi-factor risk models: factor returns, covariance and specific risk
Use an LLM coding assistant to implement a spec, then write independent tests that catch its mistakes
Learn data validation tooling and model governance basics

What to study

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

Open the roadmap

Apply

Read the full posting on MSCI’s site before applying: requirements, location and pay can change after we check them.

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.