Promote all aspects of quant strategy through in-depth exploration and research of data and statistical methods
Flexible use of the latest programming and analysis tools to extract patterns in multivariate data such as microstructure, transactions, fundamentals, and events
Applied patterns and algorithms through rigorous linear, nonlinear, and machine-learning methods including modeling
Responsible for the development, construction, testing, optimization, and risk management of strategies, as well as evaluating strategy performance
Requirements:
Strong STEM academic background in Statistics, Physics, Mathematics, Engineering, and Computer Science
3-5 years of experience in trading/machine learning/quants/data analysis
Strong in Python
Ability to excel at both open-ended research explorations and time-sensitive concrete projects
Preferred to have experience in Mid-High Frequency, Data Mining, and Machine Learning experience
Participants in competitions such as WorldQuant or Kaggle is a plus