Quant jobs / WorldQuant

Senior Quantitative Researcher

A senior researcher role building algorithmic equity models from large datasets and academic literature. It sits in WorldQuant's Yerevan research office.

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 algorithmic models for equity return prediction
Review academic quantitative finance research
Explore new datasets
Combine applied maths, computer science and financial economics

What they ask for

Required

3 years of quantitative equity research
Large dataset experience
Degree in a quantitative field
C++ and Python
Independent working
English

Preferred

Corporate actions data
Equity index basics
Olympiad medals
PhD or publications
Financial economics knowledge

Education: Degree from a top university in maths, finance, economics, CS, physics or engineering
Experience: 3 years in quantitative equity research (buy side or sell side)
Languages and tools: C++
Python
Markets: equities

How to prepare

Replicate a published equity factor and test it out of sample
Study corporate actions handling in equity data
Review asset pricing and portfolio theory
Strengthen C++ and Python for large datasets

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

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

View the posting on WorldQuant’s site ↗

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