Quant jobs / Balyasny Asset Management

Quantitative Researcher - Systematic, Multi-Asset Arbitrage (Summer Internship)

The ten-week quantitative research internship applies statistical models to investment problems. Placements can cover systematic signals, text research, arbitrage, portfolio construction or risk.

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.

Investigate signals using financial or textual datasets
Build predictive models and test research hypotheses
Develop analytical tools with researchers and portfolio managers
Explain findings and limitations to the host team

What they ask for

Required

Python
Probability and statistics
Experience with complex datasets
Independent empirical research
Predictive modelling
Technical communication

Preferred

Language-model familiarity and NLP research

Education: Bachelor or master student in maths, statistics, computing or a related quantitative subject; graduation winter 2027–summer 2028.
Experience: Ten-week student summer internship.
Languages and tools: Python
Markets: multi-asset

How to prepare

Build a reproducible predictive-model experiment
Evaluate a text-derived feature without using future information
Present a research finding with clear uncertainty and validation

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

View the posting on Balyasny Asset Management’s site ↗

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