Quantitative Trader Programme

  • BP
  • London, UK
  • Oct 04, 2019
Job - Full time Aerospace engineering Astronomy Biology Computer Science Chemical engineering Engineering Health Science Life Science Mathematics Medical Sciences Chemistry Civil engineering Physics Psychology Social Science Teaching/Academics Technology Veterinary medicine

Description

2-year Quantitative Trader Programme

Competitive Salary

Canary Wharf

BP Supply and Trading is one of the largest and most active energy trading organisations in the world. Operating in physical and financial energy markets globally, we believe it to be best-in-class. Our trading experts have unparalleled access to information across the globe. And it’s here that your curiosity and passion for monetizing statistical patterns and applying complex optimization techniques will shine.

About the programme:

You’ll work with an experienced trading desk and in close collaboration with an established team of Quantitative Analysts and Data Strategists. They will support you as you initially learn to develop trading strategies on a fast-track programme that will give you

skills in the energy industry and trading concepts. The second year will see you with your own position to manage under an experienced trading mentor. Throughout, you’ll learn to be one of the best in the field. You’ll have the autonomy to make decisions sooner - knowing that you’re surrounded by expert colleagues who want to help you succeed. At the end, you’ll be well positioned for a trading career with us. The skills you gain could also equip you for roles with our global analytics or data science teams. What’s certain is that the opportunities will be worldwide and the rewards will truly reflect your performance.

About you:

You’ll need a PhD, MSc or equivalent from a top institution, in physics, mathematics, engineering, computer science, quantitative finance or a similar subject. Beyond that, you’ll have a good grasp of probability, statistics and computer programming, plus an awareness of technological developments and their potential. The ability to make impartial risk decisions under pressure will be key. If your knowledge stretches even further to machine learning, large data set processing, financial engineering, behavioural finance or game theory, so much the better.

Experience level of the applicant we want

Some work experience, Graduate