Quantitative Researcher

Jane Street Jane Street · Quant · Hong Kong · Quantitative Research

Quantitative Researcher role at Jane Street focusing on identifying market signals, analyzing data, building and testing models, and creating trading strategies. The role involves close collaboration with experienced researchers, working with large datasets and GPU clusters, and applying various statistical and ML techniques. Interns will work on projects, learn about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets, complemented by classes on markets and trading.

What you'd actually do

  1. learn how we identify market signals, analyze large datasets, build and test models, and create new trading strategies
  2. work closely with full-time researchers on projects drawn from their own work
  3. gain a better understanding of the diverse array of challenges we consider every day, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets
  4. Your day-to-day project work will be complemented by classes on the broader fundamentals of markets and trading, lunch seminars, and activities designed to help you understand the entire process of creating a new trading strategy, from initial exploration to finding and productionizing a signal.

Skills

Required

  • logical and mathematical thinking
  • Intellectual curiosity
  • strong programmer
  • Python
  • open-minded thinker
  • precise communicator
  • collaborating with colleagues

Nice to have

  • data science
  • machine learning
  • Research experience

What the JD emphasized

  • close collaboration is essential
  • petabytes of data
  • computing cluster with hundreds of thousands of cores
  • growing GPU cluster containing tens of thousands of high-end GPUs
  • strong programmer who’s comfortable with Python

Other signals

  • quantitative research
  • machine learning techniques
  • deep learning
  • financial datasets
  • time series analysis
  • feature engineering
  • model building