Quantitative Trading Summer Analyst

Quantitative Trading Summer Analyst

Application Information


  • Put your math and programming skills to work on high impact projects
  • Experience three different quantitative trading desks
  • Discover new ways to add value for clients

Barclays makes markets in nearly all major asset classes, providing sophisticated, timely solutions to our clients. If you like work in a fast-paced, dynamic and exciting environment where you help clients make their next move by quickly processing information and anticipating market trends, then a Quantitative position in our Sales and Trading team could be the right place to start your career.


What to expect

Expect never to stand still. Initial training will give you the essentials to start, after which you’ll go straight into the first of three three-week rotations where you’ll experience different sales and trading desks across asset classes.

Through your desk assignments, you’ll develop a solid understanding of the global markets, building your communication, quantitative and analytical skills. You may:

  • build and back test mathematical models
  • monitor markets and help formulate trade ideas
  • perform various analyses on market data, fundamental data and technical data
  • attend client meetings or calls with traders, salespeople and research colleagues.

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. Senior and junior mentors will guide your progress, and networking and social events will provide a fully rounded experience.

Halfway through, you’ll get constructive feedback on your performance. 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. If you perform very well and meet our hiring criteria, you could have a full-time role waiting for you after graduation.

Who thrives here

The right candidate will have a background in one or more of the following:

  • Physics, mathematics, finance or engineering, with relevant coursework in statistics, linear algebra, and stochastic calculus
  • Machine learning
  • Optimization
  • Strength in at least one programming language (e.g. Python, C++, Java, etc.)
  • Experience with statistical software (e.g. R, Matlab, etc.)