Quantitative Researcher – Systematic Equities

We are recruiting on behalf of a small, highly collaborative, and entrepreneurial systematic investment team seeking a talented Quantitative Researcher to help expand their global systematic equities strategies. This is an outstanding opportunity to join a high‑performing group where your research will have direct impact on portfolio construction and alpha generation. The environment is fast‑paced, intellectually rigorous, and offers exceptional long‑term career growth.

Role Overview

As a Quantitative Researcher, you will work closely with the Senior Portfolio Manager and other researchers to develop, test, and refine systematic equity signals and strategies. You will contribute across the full research lifecycle—from idea generation and dataset exploration to modelling, backtesting, and deployment.

This role is ideal for someone who thrives in a lean team structure, enjoys autonomy, and brings both strong technical skills and economic intuition.

Key Responsibilities

• Collaborate directly with the Senior Portfolio Manager on alpha research, including signal discovery, hypothesis testing, and performance evaluation.
• Conduct research using diverse financial and alternative datasets, applying statistical techniques to uncover predictive relationships.
• Develop and backtest systematic equity strategies, ensuring robustness across regions, regimes, and market conditions.
• Explore and implement machine learning or NLP‑based approaches depending on your academic and research background.
• Combine strong financial intuition with statistical learning to build predictive models that directly impact trading decisions.
• Contribute to the improvement of the team’s research tools, workflows, and data‑processing pipelines.

Preferred Technical Skills

• Strong programming and research skills, especially in Python.
• Solid understanding of statistical modelling, predictive modelling, and data analysis.
• Degree from a top‑tier university in a quantitative field such as:
  • Data Science
  • Computer Science
  • Statistics
  • Applied Mathematics
  • Physics
  • Engineering
• Background in machine learning is particularly welcome.

Preferred Experience

• 1–3 years of experience within a systematic trading environment, ideally focused on equities.
• Hands‑on experience with statistical modelling and signal research for equity markets.
• Prior research applying machine learning techniques to return prediction is a strong plus.

Highly Valued Attributes

• Experience within buy‑side quantitative trading teams.
• Strong economic intuition alongside analytical depth.
• Creativity, critical thinking, and a genuine passion for exploratory research.
• Experience working with equity datasets and understanding market microstructure.
• Ability to work independently in a fast‑moving research environment while still thriving in a collaborative team structure.