Campus Quantitative Researcher / Trader (Intern)
Quantitative Research / Algorithmic Trading Internship (Amsterdam)
About the Role:
The quant research & trading internship is an intensive 10-week program focused on enhancing your quantitative and programming skills, as well as letting you experience what it’s like to be a full-time quant researcher at Jump.
At Jump our people can contribute to trading teams in the following roles, or a blend of all three: quantitative researcher / data scientist, algorithmic trader, and software developer – so our internship program is designed train you in a variety of areas. Topics include Machine Learning, trading / market mechanics, C++, statistics, and our research process for signal generation.
Applying lessons from training, you will first work with fellow interns to develop your own predictive models and automated trading strategies for live trading.
Then you’ll have the opportunity to rotate and work with several trading teams . During each rotation you’ll work on a project with the trading team while being mentored by experienced quant researchers, traders, and developers. Other duties as assigned or needed.
Who Should Apply?
We are seeking the sharpest analytical minds from top undergraduate and graduate programs. Ideal candidates have an uncommon drive to learn and improve, an entrepreneurial spirit, and strong skills in programming and/or quantitative analysis (statistics, data mining, mathematics, machine learning, etc.).
No prior knowledge of finance or trading is necessary. We’ll give you the training that you’ll need. Reliable and predictable availability required.
Although we strongly value training in Computer Science and Mathematics, we are excited to meet people with exceptional achievements in any technical discipline. Recent hires include students from fields such as Electrical Engineering, Statistics, Physics, Neuroscience, Materials Science, Operations Research, and more.
If you have outstanding skills in math and programming and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.