Quant Researcher - Systematic Equities

Quant Researcher - Systematic Equities - Dubai

We are supporting a leading global investment platform in hiring a highly skilled Quantitative Researcher.

This role will focus on building and enhancing a market‑microstructure‑driven research framework for the systematic trading of global equity strategies. The ideal candidate will combine strong statistical and programming expertise with experience handling large financial datasets in a fast‑paced, research‑driven trading environment.

Strategy Research & Development

• Collaborate closely with the Senior Portfolio Manager to design and refine systematic global equities strategies.
• Contribute to idea generation, hypothesis testing, and alpha research.
• Conduct end‑to‑end research including data gathering, cleaning, feature creation, modeling, and backtesting.

• Work hands‑on with multiple exchange data sets, ensuring high‑quality data pipelines through assessing, cleaning, and building features.
• Analyze large, complex datasets using advanced statistical learning techniques and market‑microstructure methods.
• Implement scalable, flexible, and efficient data‑extraction frameworks using existing tools.
• Optimize Python and C++ code to support high‑scale systematic research workflows.
• Create new data features and extend existing research infrastructure.

• Strong expertise in Python (data analysis, scientific computing, statistical modeling).
• Proficiency with modern data science tooling:
• Experience with C++ (preferred for feature creation and performance‑critical components).
• Strong understanding of:
• Quantitative finance
• Probability theory
• Regression and statistical modelling
• Mathematical foundations behind systematic trading strategies
• Ability to clearly communicate complex research outputs to stakeholders.

• 2+ years working in a systematic trading environment, ideally focused on equities.
• Experience handling and transforming multiple vendor or exchange datasets, including assessing, cleaning, and creating predictive features.
• Track record of collaborating with PMs, engineers, and researchers in a fast‑paced, iterative environment.

• Strong intuition for the predictive power of features and datasets.
• Exceptionally rigorous, detail‑oriented, and self‑driven approach to research.
• Ability to work independently while contributing to a collaborative research environment.
• Curiosity, intellectual agility, and motivation to grow rapidly.