Campus Quantitative Trader (Intern)
About this role
Jump Trading is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
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 trader 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 / or 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, Economics, Econometrics, 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.
Company at a glance
For more than 25 years, Jump Trading has been home to people who see trading as the most fascinating problem in the world and want to solve it from every angle.
Headquartered in Chicago with 13 offices across 8 countries, we operate across asset classes, time zones, and horizons. If it trades, we want to trade it.
We are traders, engineers, and researchers working side by side to build the systems that move global markets. Our culture is built on curiosity, precision, and relentless iteration. We care deeply about impact, collaboration, and solving problems few ever get to see.
At Jump Trading, AI and machine learning are central to how we trade and build. We design and deploy advanced models, infrastructure, and tools to operate at scale in high-stakes, adversarial environments. From low-latency systems to cutting-edge research, we push the boundaries of what is possible.
We are also committed to the next generation of talent. Our student programs, from internships to our fully funded PhD Fellowships, provide hands-on experience, mentorship, and opportunities to do meaningful work. We support students at leading conferences worldwide and invite them to work with our teams on real-world challenges.
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