Quant Research

Dates: 28th June - 3rd September 2027. We are unable to facilitate any other dates or longer periods. 

Location: This internship is only available in our London office. 

We are seeking highly motivated and talented individuals for our Quantitative Research Internship in London. This is an exciting opportunity to work with a team of experts in the field of quantitative finance and gain hands-on experience in a dynamic and innovative environment. 

Key Responsibilities: 

• Collaborate with our mentors to develop and implement mathematical models and algorithms. 

• Analyse large datasets to identify trends, patterns, and opportunities for investment strategies. 

• Present findings and insights to team members and contribute to strategic decision-making. 

About the team

Marshall Wace is a leading provider of alternative investment solutions, managing quantitative, systematic, and fundamental strategies with a focus on long/short equity. Our strategies are implemented globally, leveraging proprietary systems and processes. Technology and data have been at the core of our business for more than two decades. In 2002, we launched MW TOPS, the world’s first ‘Alpha Capture’ application. Today, we continue to foster an environment focused on innovation and the pursuit of excellence. 

Our quantitative researchers are a group of talented individuals with specialisations in a range of subjects including maths, physics, engineering, and computer science. They are responsible for conceptualising, developing, and analysing models for use in our quantitative and systematic strategies as well as our electronic trading processes. They look to reduce risk and cost while maximising returns, with access to a wealth of tools designed to help them build complex models with ease. 

What we're looking for 

• Academic achievement: Currently enrolled in a penultimate year of a Master's or PhD program in a STEM subject, set to finish in 2028. 

• Strong numeracy: Strong mathematical skills with a solid understanding of statistical methods and data analysis. 

• Superior technical skills: High proficiency in programming languages such as Python, R, or MatLab. 

• Create value: Excellent problem-solving abilities and attention to detail. 

• Team player:  Strong communication skills and the ability to work collaboratively in a team environment.