Quant jobs / Maven Securities

Quantitative Trading Analyst

A role in the Market Intelligence team turning trading data into analytics, tools and recommendations for portfolio managers. It sits between research, technology and trading in a proprietary firm.

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.

Analyse trade and strategy performance and decompose PnL drivers
Build Python libraries that standardise performance metrics across desks
Detect alpha decay, parameter inefficiency and execution drag
Create automated reports and AI tooling for PMs
Monitor exposures and flag emerging risks

What they ask for

Required

2-5 years at a hedge fund, prop firm or quant manager
Strong Python (Pandas, NumPy, SciPy)
SQL
Trade lifecycle knowledge
Understanding of relative value, stat arb or volatility strategies
Strong numerical skills

Preferred

Understanding of AI governance in finance
Interest in improving strategies
Wider market interest

Education: Not stated
Experience: 2-5 years at a hedge fund, proprietary trading firm or quantitative asset manager
Languages and tools: Python
SQL
Markets: options, multi-asset

How to prepare

Build a PnL attribution notebook that splits returns by signal, execution and risk
Practise analysing alpha decay on a simple strategy
Learn the trade lifecycle from order to settlement
Write a reusable Python package for performance metrics

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

View the posting on Maven Securities’s site ↗

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