2027 Quantitative Developer Intern, London

2027 Quantitative Developer Intern, London If you are interested in more than one business or office location, you may submit a maximum of 2 applications.

London, United Kingdom Job Title 2027 Quantitative Developer Intern – London About Millennium Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors. Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact. Meet the Team Quantitative Developers work at the intersection of technology, quantitative research, and trading, building the tools, infrastructure, and analytics that help bring models into production, strengthen decision-making, and support trading activity at speed and scale. What You’ll Do Design and develop production systems for model deployment, serving, and monitoring at scale Build APIs and services that expose statistical models, risk calculations, and portfolio analytics to trading systems Productionize research models by optimizing performance, strengthening error handling, and ensuring numerical stability Develop high-performance infrastructure for real-time pricing, risk calculations, and portfolio optimization Build data pipelines and quantitative tools that support back-testing, statistical analysis, market simulation, and model inference What You Bring Graduating between December 2027 to July 2028 Pursuing a Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative field Strong programming skills in Python, C++, or Java, with a focus on writing production-quality code Solid understanding of data structures, algorithms, and system design principles Knowledge of probability, statistics, and numerical computing methods