Trading Quantitative Developer in Chicago, IL at Open Systems Technologies

Date Posted: 1/16/2020

Job Snapshot

  • Employee Type:
  • Location:
    Chicago, IL
  • Job Type:
  • Experience:
    At least 5 year(s)
  • Date Posted:

Job Description

Our client is seeking a Trading Quantitative Developer who will develop programming features within a software-based trading platform which contains multiple novel performance and scalability optimizations. This client's software platform is a unique, low latency, high performance system.


  • Research projects associated with latency prediction and algorithmic improvement 
  • Determine methods to store and analyze very large amounts of data 
  • Develop tools to evaluate market data to help improve trading strategies performance
  • Investigate and design data mining and machine learning algorithms
  • Research the purpose of modeling and forecasting future price actions and volatility
  • Build and expand the current revenue base 
  • Execute and implement quantitative investment strategies
  • Develop and supporting a scalable quantitative research framework using Python, C++, and other software systems
  • Evaluate risk/reward and performance attribution across multiple asset classes
  • Design and develop applications based on the business  requirements for algorithmic trading
  • Design, develop and implement high-performance trading applications, ranging from front-end applications to black box systems
  • Use C++, Python, and other software and systems to access applications that can identify and manage portfolio risk
  • Build and enhance market prediction models for portfolios utilizing quantitative problem solving and advanced statistical techniques
  • Analyze data, creating and evaluating trading strategies


  • 5+ years hands on experience in Statistics and Machine learning
  • Strong Python experience
  • Excellent problem solving abilities
Job category:
  • Information Technology
Job keywords:
  • Trading
  • Quantitative
  • Developer
  • Machine Learning
  • C++
  • Python
  • Risk