As a Quant Trading Analyst within our Market Intelligence team, you will sit at the intersection of research, technology, and trading. You will turn raw trading data into high-value insights, build the analytics and AI tooling that Portfolio Managers (PMs) rely on daily, and deliver data-backed recommendations that materially and measurably improve PnL.
Analyse performance at trade and strategy level, deliver data-backed recommendations to PMs, and maintain follow-through to implementation and outcome measurement.
Develop and standardise tools that generate high-value insights, and establish an AI foundation that accelerates PMs' day-to-day decision-making.
Build a trading framework applied across multiple global strategies, identify style drift early and escalate to PMs and the HoMI, and document research in a reproducible format.
Develop advanced analytics infrastructure - Engineer scalable Python-based libraries and tools that standardise performance metrics across the group, and create automated workflows that convert raw trading data into insights for PMs and the Investment Committee.
Perform rigorous statistical analysis on trade- and portfolio-level data to decompose PnL drivers, and identify alpha decay, parameter inefficiencies, and execution drag to deliver actionable research.
Requirements
Nice to have: AI governance and compliance understanding
