Quantitative Researcher, High Frequency Trading

About the role

Research and develop predictive signals and high-frequency trading strategies for cryptocurrency and equity markets using large-scale market microstructure data and machine learning. Take strategies from initial research through backtesting and live trading, monitor their performance, and collaborate with engineering on features, execution, and latency. Candidates should have a track record of building high-frequency trading or statistical arbitrage signals or strategies with a Sharpe ratio of at least 2.5, as well as experience applying machine learning to high-frequency market data. Strong Python skills are required; C++ is a plus, and candidates should be able to discuss past results within applicable confidentiality limits.