Campus Quantitative Researcher, Phd (intern)

Jump Trading Jump Trading · Quant · Chicago, New York City · Front Office

Jump Trading is seeking a PhD Quantitative Researcher Intern to conduct research in financial markets, focusing on predictive modeling, alpha research, and improving live trading models and systems. The role involves end-to-end project ownership, data exploration, feature engineering, model building, fitting, evaluation, and presentation, with mentorship from experienced researchers. The program is designed to provide real-world research experience in a collaborative and innovative environment.

What you'd actually do

  1. 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
  2. Collect, clean, and explore large datasets (some clean, some noisy, some very noisy) and engineer features that turn raw data into predictive signal
  3. Build, fit, and evaluate models on our supercomputing grid, and present your results to your team throughout the summer, culminating in a final presentation
  4. Receive daily 1:1 mentorship from experienced quant researchers, with growing autonomy and compute as the summer progresses

Skills

Required

  • Currently pursuing a PhD in Statistics, Mathematics, Computer Science, Physics, or any highly quantitative field
  • Systematic research thinking: the ability to form well-educated hypotheses, design rigorous tests, and draw statistically sound, generalizable conclusions
  • Ownership of your research: the ability to explain the choices you made, the alternatives you considered and rejected, and why your approach won
  • 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
  • Creativity and initiative to explore ideas beyond those suggested to you
  • Perseverance: successful research is the result of lots of failure and intellectual risk-taking

Nice to have

  • Proficiency in C++
  • Familiarity with financial markets

What the JD emphasized

  • real-world project tied to live business needs
  • rigorous tests
  • statistically sound way
  • fully understood result
  • live market itself
  • real-world data
  • statistically sound, generalizable conclusions

Other signals

  • deep learning models in production
  • predictive modeling
  • alpha research
  • improving the models and systems behind live trading