Machine Learning Researcher

Jane Street Jane Street · Quant · Hong Kong · Machine Learning

Jane Street is seeking a Machine Learning Researcher to work on projects combining novel ML ideas with systematic trading strategies. The role involves end-to-end studies, exploring new modeling paradigms, and applying state-of-the-art techniques to challenging problems in finance, utilizing large-scale data and computing resources. The position is for a PhD student or postdoc with empirical ML research experience, strong logical and mathematical thinking, and Python implementation skills.

What you'd actually do

  1. conduct an end-to-end study of an unexplored dataset
  2. try a new modeling paradigm for a thorny problem
  3. consider blue-sky approaches that we’re still trying to figure out
  4. diving deep into market data
  5. tuning hyperparameters
  6. debugging training issues
  7. analyzing the predictions your model makes

Skills

Required

  • PhD student or postdoc working on empirical ML research problems, or someone with equivalent research experience
  • applying logical and mathematical thinking to all kinds of problems
  • applying state-of-the-art techniques drawn from many problem domains
  • implement and iterate on your ideas in Python and your favorite ML framework
  • Fluent in English

Nice to have

  • Curious about the machine learning landscape
  • Fluent with a versatile set of models and tricks
  • Eager to ask questions, admit mistakes, and learn new things

What the JD emphasized

  • novel ML ideas
  • systematic trading strategies
  • novel techniques
  • empirical ML research

Other signals

  • novel ML ideas
  • systematic trading strategies
  • petabytes of data
  • hundreds of thousands of cores
  • tens of thousands of high-end GPUs
  • large models
  • nonstationary datasets
  • competitive multi-agent environment
  • novel techniques