Quantitative Developer│ PhD and Post Doc. Graduates

1 day ago


London, Greater London, United Kingdom Selby Jennings Full time £80,000 - £150,000 per year

We are seeking exceptional Computer Science PhD and post-doctoral graduates from Tier 1 universities to join a dynamic and innovative quantitative team at a leading hedge fund in London as Quantitative Developers, specialising in cutting-edge systematic strategies.

After several successful years, they are now looking to onboard PhD and post-doctoral graduates available to start in 2026. This is an exciting opportunity to work at a tier-1 hedge fund, contributing to the development of advanced quantitative techniques and high-performance frameworks.

You will build and enhance software and frameworks to support existing strategies and develop new signals and models. Additionally, contribute innovative ideas to research and design fast predictors and simulation frameworks. You will be closely collaborating with world-class researchers and in a fast paced environment.

Key Responsibilities

  • Design and implement quantitative models to support trading strategies and risk management.
  • Research and apply new machine learning techniques to improve predictive accuracy.
  • Collaborate with quantitative researchers and traders to translate mathematical models into robust, production-ready systems.
  • Optimise algorithms for speed and scalability, ensuring low-latency execution in real-time environments.
  • Perform rigorous testing and validation of models and systems to ensure accuracy and reliability.
  • Maintain and enhance the existing codebase, ensuring compliance with best practices and coding standards.

Qualifications

  • PhD in Computer Science or a closely related computational discipline.
  • Strong programming skills in Python; experience with C++ is highly beneficial.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work independently and as part of a collaborative team.

Preferred Qualifications

  • Experience with cloud technologies.
  • Exposure to large, fast-paced datasets.
  • Knowledge of global macroeconomic factors and their impact on financial markets.


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