Campus Quantitative Researcher (Intern)
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Overview
Jump Trading is looking for a Campus Quantitative Researcher Intern in Singapore. This role involves building predictive models and developing algorithms for automated trading. Ideal for analytical minds from top programs. Jump Trading Group 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
- •Build predictive models from big data.
- •Develop algorithms to automatically execute trades in financial exchanges.
- •Contribute as a quant researcher, data scientist, trader, and software developer.
- •Participate in a 10-week internship program with training in trading, programming, and quant research.
- •Work on research projects with mentorship from experienced quants/traders.
- •Help build predictive models and devise automated trading strategies.
Conditions
*Candidates should be interested in working in Singapore for their full-time job after graduation. *Timing of application consideration and interviews will vary to accommodate university timelines.
Who Should Apply?
- •Sharp analytical minds from top undergraduate and graduate programs.
- •Strong skills in programming and/or quantitative analysis (statistics, data mining, mathematics, machine learning, etc.).
- •No prior knowledge of finance or trading is necessary.
- •Reliable and predictable availability required.
- •Training in Computer Science and Mathematics is valued, but exceptional achievements in any technical discipline are welcome.