Quant jobs / Brevan Howard

2027 Summer Internship – Systematic Trading

A summer internship with Brevan Howard's systematic portfolio management teams, covering signals, backtests and market models. It sits within a macro hedge fund and is aimed at research-minded postgraduates.

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.

Develop and backtest trading signals for a portfolio management team
Build market-related models and test how they behave out of sample
Research and write up new trade ideas with supporting data
Add pipelines and analyses to the shared analytics library
Use LLM tools for coding and research on the desk

What they ask for

Required

PhD candidate or first-year master's student
Strong maths and quantitative problem-solving
Python programming
Excel and VBA
R
Interest in financial markets and products
Clear written and spoken English

Education: PhD candidate or first-year master's student, finishing before July 2028
Experience: Students; no prior experience stated
Languages and tools: Python
R
VBA
Excel
Markets: multi-asset, fx, fixed-income, credit

How to prepare

Build and backtest a cross-asset trend or carry signal in Python, with realistic costs
Learn the common backtest traps (overfitting, look-ahead, survivorship) and test for them
Study the basics of bonds, rates derivatives, FX and credit
Write a two-page research note on one trade idea backed by data
Read a standard text on systematic macro or time-series momentum

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

View the posting on Brevan Howard’s site ↗

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