Location
London or Dublin

Hours
Full Time - 12 weeks starting June 2027

Salary
Negotiable

About the Role
Our Quantitative Services Summer Internship Programme at London Stock Exchange Group (LSEG) offers a unique opportunity to experience a career within the Quantitative Services team of Post Trade Solutions. As an intern, you will contribute to the development and implementation of the Open-Source Risk Engine (ORE) and its dependent services, supporting major financial institutions with advanced risk management solutions. This role involves working closely with a team of quantitative analysts to develop risk analytics services, pricing client portfolios, performing stress-testing and backtesting, and collaborating with collateral management and risk teams to build financial applications. The internship is designed to provide hands-on experience and insight into quantitative finance within a leading global financial markets infrastructure and data provider. You will be part of a dynamic and inclusive culture that values innovation, integrity, and continuous improvement, with hybrid working arrangements and a commitment to sustainability and community engagement.

Experience
Penultimate year of graduate study, due to complete degree on or before summer 2028. Experience or demonstrated interest in quantitative finance through studies, projects, or independent work.

About you
Interest in Financial Engineering and quantitative finance. Strong collaboration and communication skills. Curiosity for data analysis and problem-solving. Ability to work effectively in a team environment. Eligible to work in London or Dublin without restrictions for the duration of the internship.

Qualifications
Predicted PhD or master’s degree in Mathematics, Physics, Financial Engineering, or other quantitative fields. Good understanding of Python or C++. Familiarity with Git and LaTeX is ideal but not essential. Functional knowledge of stochastic models/SDEs such as Ornstein-Uhlenbeck, Hull-White, Black-Scholes models. Knowledge of financial derivatives and pricing techniques including finite difference and Monte Carlo simulation.