Quantitative Researcher – Systematic Equities

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.

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.

• 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.

• 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.

• 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.

• Experience with in 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.