Market Taking

Market Taking — Quantitative Developer

Applications open

Turn your desk's trading ideas into working signals and order logic. You will collaborate with four trader/researchers and the Head of Desk, building team strategies on the runtime and research tools provided by Technology.

What you'll do

Arm: Market Taking · Places: 2 per team · Team size: 7

About QTE

Queen's Tower Exchange is a financial-markets simulation for Imperial College London students. Student teams build and trade strategies using live data and simulated capital.

Responsibilities

Implement and test signals, position sizing, entries and exits.
Track orders and positions across partial fills and delayed responses.
Build strategy stops and recovery after cancellations or connection failures.
Compare realistic execution outcomes with research assumptions.
Keep results reproducible through code versions and recorded configurations.

What success looks like

Reliable strategy implementations that make live behaviour understandable and give the team useful evidence for improvements. The desk is scored on risk-adjusted returns and net profit and loss; software quality supports both.

Prerequisite knowledge

Confidence writing and debugging programs in Python or another general-purpose language.
Basic familiarity with data structures, version control and tests.
A completed coding project from coursework, personal work or a team activity.
Interest in understanding the reasoning behind the strategy you implement.

You do not need previous finance employment or a trading system of your own.

Useful, but not required

Python data libraries, APIs, event-driven systems or backtesting experience.

What you'll be taught

Much of your learning will take place during a dedicated training week, held after teams are selected and before trading begins. Your Head of Arm will deliver lectures exclusively for the teams in your arm, giving you a strong grounding in the concepts and tools you will use in your role.

How trading signals become orders and positions.
The QTE runtime, strategy registration, backtester and session records.
How spreads, fees, delays and finite liquidity change a strategy's results.
How to implement trading-specific controls and respond to risk restrictions.
How to work with researchers on experiments that can be reproduced and compared.

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