• Applying minute data and real trading experimentation to define strategy decision-making
• Assisting in development of a robust functional trading strategy, inputs the market data and outputs the trading signals to markets for timely execution
• Refining, and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components
• Web scraping and API data, cleaning, reformatting and storage
• Responsible for trading systems development, which includes connectivity, maintenance, and internal automation processes
• Troubleshoot and resolve any systems related issues and handle the release of code fixes and enhancements
• Maintaining the production and research systems and software setup, ensuring its stability, robustness and security
• Researching and implementing performance analytics, including signal performance and post-trade analytics (e.g. slippage, fill-rate, and market impact reports)
• Experience with Machine Learning applications using scikit-learn, Keras, and TensorFlow
• A bachelor’s or advanced degree in a highly quantitative subject such as Computer Science, Engineering, Physics, Finance, Statistics, or Mathematics.
• Experience in Python, Machine Learning.
• Exceptional quantitative as well as programming skills.
• Motivation and resourcefulness in quickly solving hard problems through the creative application of technology.
Qualities that make great candidates:
• Strong interest in digital assets and the role they play in the future of financial markets
• Aptitude for numerical and quantitative analysis skills
• Problem-solver that can consistently provide creative solutions in a constantly changing market