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Campus Quantitative Researcher, PhD (Intern)

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 incenting 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.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

About the Role

The PhD quant research internship is an intensive 10-week program designed to show you what it's like to do research at Jump: real problems, real data, real markets. The program runs in person during Summer 2027 in our Chicago and New York offices. The first two weeks are focused training covering our research process, machine learning, statistics, trading and market mechanics, Python, and the infrastructure you'll use all summer. From there, you'll be matched with a trading team based on your background and interests, and spend the remaining weeks working 1:1 with experienced researchers on a real-world project tied to live business needs. You'll learn the craft working alongside people who have spent years practicing it.

Research at Jump spans every asset class and a full range of time horizons, from high frequency to strategies that hold for days and weeks. Teams work across the spectrum of methods, from hand-crafted signals and rigorous classical statistics to deep learning models in production. Your project will reflect your team's needs, but the craft is the same everywhere: form well-educated hypotheses, construct rigorous tests, interpret results in a statistically sound way, and when an idea fails, understand why before moving on. One excellent, fully understood result is worth more here than a dozen shallow ideas. And every result is tested where it counts: against the live market itself.

The program is open to currently enrolled PhD students. The internship is one of the main pathways to a full-time offer at Jump Trading.

What You'll Do

• Match with a trading team and own a research project end to end, in areas such as predictive modeling, alpha research on new datasets, and improving the models and systems behind live trading
• Collect, clean, and explore large datasets (some clean, some noisy, some very noisy) and engineer features that turn raw data into predictive signal
• Build, fit, and evaluate models on our supercomputing grid, and present your results to your team throughout the summer, culminating in a final presentation
• Receive daily 1:1 mentorship from experienced quant researchers, with growing autonomy and compute as the summer progresses
• Other duties as assigned or needed.

Skills You'll Need

• Currently pursuing a PhD in Statistics, Mathematics, Computer Science, Physics, or any highly quantitative field; recent researchers have come from fields as varied as Electrical Engineering, Operations Research, and Economics
• Systematic research thinking: the ability to form well-educated hypotheses, design rigorous tests, and draw statistically sound, generalizable conclusions. No matter your area, these are the fundamental aspects of a good researcher, and it is no different at Jump Trading.
• Ownership of your research: the ability to explain the choices you made, the alternatives you considered and rejected, and why your approach won. Every idea demands a premise, and every rejection deserves a reason
• Experience conducting an in-depth research project with real-world data
• Programming experience in Python, with the ability to read, understand, and debug code, including code you didn't write
• Communicative and collaborative working style, sharing results early and often and treating mentors' time as a resource to use, not conserve
• Creativity and initiative to explore ideas beyond those suggested to you, with the judgment to bring your team along as you do
• Perseverance: successful research is the result of lots of failure and intellectual risk-taking, and a PhD is often proof that you can stay with a hard problem for years without quitting

Nice to have:

• Proficiency in C++ (either works, and both is better)
• Familiarity with financial markets. No prior knowledge of finance or trading is necessary; we will give you the training that you need
• Reliable and predictable availability required.

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role is $300,000 per year.