Quantitative Researcher | Trading Team

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.

We’re expanding our successful global equity stat arb business with the build out of a new team of quantitative researchers focused on developing mixed-frequency (low/mid) strategies based out of Hong Kong. This team will leverage new and differentiated approaches to research and will be comprised with top talent across the fields of Quantitative Research, ML/LLM & Engineering.

What You'll Do: 

Quantitative Researchers collect and analyze tens of thousands of data sets, identify patterns and extract insights into the complexities in global financial markets. Researchers lean heavily on statistical analysis, machine learning, and data engineering skills; applying the results of their research to forecasts and predictive trading models. Jump’s Quantitative Researchers are constantly collaborating with other scientists, traders, hardware and software developers, and market facing business teams to push for the best expression of our new ideas.

Skills You'll Need:

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  Creative thinkers who are driven, self-motivated, and eager to solve challenging problems

  
  


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  Proven experience developing successful quantitative trading strategies is highly preferred, though not required

  
  


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  Demonstrable experience leveraging forecasting and machine learning techniques, such as linear regression analysis, neural networks or other state-of-the-arts models

  
  


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  Bachelor, Masters or PhD in Computer Science, Statistics, Physics, Mathematics (or related subject)

  
  


• Strong programming skills in C++/python in a Linux environment 


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  Desire to work within a collaborative, team-driven, fast-paced environment