Quantitative Analytics Summer Associate

Quantitative Analytics Summer Associate

Application Information


  • Tackle fascinatingly complex projects as part of an industry leading team
  • Contribute to some of our most exciting technological advancements
  • Sharpen your technical skills and see how much of an impact they can make

Our Quantitative Analytics team is an integral part of the bank that provides model development, analytics and expert advice across Barclays. You'll help deliver solutions for derivatives pricing, risk management, capital utilization and fraud detection; all using the latest model development approaches and advancements in technology.


Meet our people

What to expect

Expect to be challenged. Following initial training, you’ll become an integral part of our expert team, helping deliver intricate solutions for everything from derivatives pricing and risk management to capital utilization and changes in market structure. Your work will be highly technical, and could see you tackling challenges such as:

  • applying quantitative techniques to solve real world business problems
  • researching, developing and implementing new models and solutions
  • improving our computing or data infrastructure.

How you’ll develop

Throughout the summer, our support will help you deliver your best work. In our team-driven environment, you’ll find that mentoring happens naturally and friendships are easy to form. Mentors will guide your progress, and networking and social events will provide a fully rounded experience. By the time the summer’s over, you’ll walk away with a solid understanding of our business, our culture and your potential place within it. We offer full time employment opportunities to those interns who demonstrate an excellent work ethic and technical competence during their time with us.

Who thrives here

Logical problem-solvers do well here. We also look for mathematical and programming skills —particularly C++, Python or R — along with a background in a discipline such as Physics, Mathematics, Quantitative Finance, Statistics or Computer Science.