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Quantitative Developer

London

Engineers Gate is a leading quantitative investment firm focused on systematic trading in global financial markets. Our team of researchers, developers, and financial industry professionals apply sophisticated statistical and machine learning models to uncover predictive signals in data and turn them into superior investment returns. We believe that career fulfilment and enterprise success converge when smart, hard-working, and intellectually curious people come together in pursuit of innovation and excellence.

The Quantitative Developer will join our London Portfolio Management group and play a key role in building and scaling its central infrastructure. The work spans greenfield projects as well as enhancing and refactoring existing systems, offering immediate group-wide impact and exposure to every area of the trading system and research platform. We place a high value on continuous learning, and this role is a rare opportunity to work alongside and learn from highly experienced quantitative developers and researchers in a collaborative and innovative group. A successful candidate will combine strong numerical and engineering skills with a genuine appetite for learning new technologies. They will be comfortable working independently from high-level guidance. If you thrive in a collaborative environment, follow best practice across the full software development life cycle, and want to make a meaningful impact, we encourage you to apply.

Key Responsibilities

  • Build, maintain, and monitor the existing live trading infrastructure.
  • Develop and enhance the research platform and analytics tooling.
  • Collaborate with researchers to bring new trading strategies into production.

Required Skills, Qualifications and Experience

  • Undergraduate degree in Computer Science or a related STEM discipline.
  • Production-level software engineering experience in a high-quality, technology-driven environment.
  • Solid understanding of algorithms, software architecture, design patterns, and software engineering best practices.
  • Proficiency in at least one modern programming language (e.g. Python, C++, Java).
  • Strong numerical reasoning and problem-solving skills, with the ability to work comfortably with quantitative and scientific problems.

Desirable Skills and Experience (beneficial but not required)

  • Experience with Python and/or MATLAB for numerical and scientific computing.
  • Familiarity with AI-assisted development tools.
  • Experience working with machine learning and quantitative research workflows.
  • Exposure to cloud platforms, especially AWS

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