Quant jobs / Voleon

Member of Research Staff – Causal Inference, Voleon Securities

A causal inference research role at a new ML-led securities business. The person models market behaviour and microstructure using synthetic and live experiments.

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.

Apply causal methods to market microstructure data
Improve models of how the market responds to trades
Run synthetic and live trading experiments
Track the causal inference literature for new methods

What they ask for

Required

Causal inference and statistics background
Top-tier publication record
Strong mathematics
Production Python
PhD-level coursework

Preferred

PhD in a relevant field

Education: PhD-level coursework required; PhD in a relevant field preferred
Experience: Strong causal inference research record
Languages and tools: Python

How to prepare

Study causal inference methods such as instrumental variables and potential outcomes
Read about price impact and how to estimate it
Design a simple randomised experiment on simulated markets
Learn market microstructure basics

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 Voleon’s site before applying: requirements, location and pay can change after we check them.

View the posting on Voleon’s site ↗

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