Quantitative Researcher – Orderbook Signal Generation

About the role

We are seeking a Quantitative Researcher to develop order‑book‑driven predictive signals. The role is ideal for early‑career professionals with hands‑on experience analysing limit order‑book data and a strong curiosity about market microstructure.

Key responsibilities

• Analyse high‑frequency limit order‑book data to uncover patterns, inefficiencies and predictive signals.
• Build and back‑test quantitative models using historical tick and order‑book data.
• Collaborate with senior researchers and traders to translate findings into production‑ready strategies.
• Develop and maintain data pipelines for processing large‑scale, high‑frequency market data.
• Apply statistical and machine‑learning techniques, especially tree‑based methods, to improve signal quality.
• Continuously monitor and iterate on live signals and models based on performance.

Required profile

• 1–3 years of professional or research experience working directly with order‑book data.
• Technical degree in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, Engineering or Financial Engineering.
• Strong proficiency in Python and standard data‑science libraries (pandas, NumPy, etc.).
• Genuine interest in financial markets and market microstructure.
• Solid foundation in statistics and quantitative analysis.
• Excellent problem‑solving skills and ability to communicate technical findings to non‑technical stakeholders.

Required skills

• Python programming.
• Data manipulation with pandas and NumPy.
• Statistical analysis.
• Machine‑learning techniques, including tree‑based methods.
• Development of high‑frequency data pipelines.