Machine Learning Researcher

Jane Street Jane Street · Quant · New York, NY · Machine Learning

Research internship focused on applying novel ML ideas to systematic trading strategies, working with large models on nonstationary datasets in a competitive multi-agent environment. Involves end-to-end studies, new modeling paradigms, and blue-sky approaches.

What you'd actually do

  1. work side by side with experienced ML Researchers on projects that we’ve selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies
  2. conduct an end-to-end study of an unexplored dataset
  3. try a new modeling paradigm for a thorny problem
  4. consider blue-sky approaches that we’re still trying to figure out
  5. diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes

Skills

Required

  • Python
  • ML framework

Nice to have

  • logical and mathematical thinking
  • curious about the machine learning landscape
  • apply state-of-the-art techniques
  • versatile set of models and tricks
  • implement and iterate on your ideas
  • ask questions
  • admit mistakes
  • learn new things

What the JD emphasized

  • novel ML ideas
  • real-world systematic trading strategies
  • large models
  • nonstationary datasets
  • competitive multi-agent environment
  • novel techniques
  • practical models
  • practical experience working on ML problems

Other signals

  • novel ML ideas
  • systematic trading strategies
  • large models
  • nonstationary datasets
  • competitive multi-agent environment
  • novel techniques