Quantitative Researcher

Kernel Trading Technologies started as a trading group in a hedge fund and is built on a successful track record of trading systematic strategies powered by scientific and cutting-edge technologies. The team is consisted of successful portfolio managers from top quantitative funds, top-notch machine learning researchers, statistics professors from academia and excellent technologist previously from high-frequency trading space. The team focuses on statistical arbitrage strategies trading global futures and has achieved high return and Sharpe every single year since inception.

We are constantly looking for improvements to power and evolve our research and trading platform to expand our success story.

We are seeking highly qualified and talented Quantitative Researchers to join our dynamic team. In this role, you will work closely with our team of portfolio managers, quantitative developers and technologists to develop and improve upon our proprietary trading models and strategies. You will have the opportunity to apply your skills in data analysis, statistical modeling, and machine learning to real-world financial data, and contribute to the success of our trading operations.

• Develop, test, and implement quantitative models for our trading strategies, using advanced statistical techniques and machine learning models
• Analyze large datasets to identify trading opportunities and improve model performance
• Collaborate with quantitative developers to implement models and strategies in our trading system
• Conduct research to stay current on market conditions and industry trends
• Communicate complex quantitative concepts and their implications to non-technical team members

• Advanced degree in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, or Engineering
• Strong programming skills, preferably in Python or C++
• Solid understanding of probability, statistics, and machine learning
• Understanding of data structures, algorithmic complexities, and numerical algorithms
• Ability to communicate effectively in a collaborative, complex and highly technical team environment
• Intellectual curiosity and passion for solving challenging problems using technology