Location
London or Dublin

Hours
Full Time - 12 weeks starting June 2027

Salary
Negotiable

About the Role
Our Quantitative Services Summer Internship Programme offers a unique opportunity to experience a career within the Quantitative Services team of Post Trade Solutions at London Stock Exchange Group (LSEG). As an intern, you will contribute to the success of our organisation by working on cutting-edge risk analytics and financial applications. The role involves supporting the development of the Open-Source Risk Engine (ORE) and its dependent services, assisting with infrastructure for the IM Risk Generation (IMRG) service, pricing client portfolios, and performing stress-testing and backtesting using ORE. You will also translate client portfolios into the ORE XML format and collaborate with collateral management and risk teams to build innovative financial solutions. This internship is designed for penultimate year graduate students with a strong quantitative background, offering hands-on experience in a dynamic, global financial markets infrastructure environment. You will be part of a team dedicated to delivering transparent, state-of-the-art risk management solutions to major financial institutions.

Experience
Interest in Quantitative Finance demonstrated through academic studies, projects, or independent work. Familiarity with Python or C++ programming languages. Knowledge of stochastic models/SDEs such as Ornstein-Uhlenbeck, Hull-White, or Black-Scholes models. Understanding of financial derivatives and pricing techniques including finite difference methods and Monte Carlo simulation is highly desirable.

About you
A collaborative team player with strong communication skills. Curious about data with the ability to analyse information, draw conclusions, and propose solutions. Passionate about pursuing a career in Financial Engineering and eager to learn about the full breadth of the business. Able to work in London or Dublin without restrictions for the duration of the internship. Demonstrates integrity, excellence, and a commitment to how achievements are attained.

Qualifications
Currently in penultimate year of graduate study, expected to complete degree on or before summer 2028. Predicted PhD or master’s degree in Mathematics, Physics, Financial Engineering, or other quantitative fields. Familiarity with Git and LaTeX is ideal but not essential.