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*Candidates for this off-cycle internship should be graduating in 2026 and be interested in working in Shanghai for their full-time job after graduation.
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About the Role:

We build predictive models from big data and develop algorithms to automatically execute trades in dozens of financial exchanges around the world.

At Jump you will have the opportunity to contribute in a blend of three roles – quant researcher / data scientist, trader, and software developer – based on your incoming skills and background, interest and curiosity, and the new skills and industry knowledge that you will learn at Jump.

You will receive training, coaching and mentorship from experienced quants/traders to successfully apply skills in a variety of areas like Machine Learning, Trading / Market Mechanics, Statistics, Python, and C++. You will help build predictive models, leveraging one of the largest supercomputers in the world, and devise automated trading strategies to test in the markets against world-class competition. Other duties as assigned or needed.

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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.

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If you have outstanding skills in math, ML, and programming and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.

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