Responsibilities:

Develop new algorithmic trading strategies
Work closely with the Portfolio Managers to research, backtest, implement, and monitor profitable low- and high-frequency statistical arbitrage trading strategies for equities
Development, research, maintenance and risk management of quantitative high frequency automated equity trading strategies.
Design, calibrate and analyze quantitative pricing, trading and risk control for algorithmic strategies.
Improve the performance of existing strategies with techniques from machine learning and statistics
Develop statistical tools to manage models and for portfolio optimization.
Work closely with Portfolio Managers on trading ideas and model enhancements
Work closely with software teams on functional requirements, documentation and model testing

Requirements:

Advanced Quantitative Degree in Statistics or Math
Must have 5+ years of financial markets model development experience
Programming-Python preferred or other scripting languages (R, Matlab), SQL databases
Experience working on algorithmic/automated trading models

Keywords: High Frequency, Equity, Trading Strategist, Statistical Modeling, Automated Trading, Risk Management, Portfolio Optimization

Please send resume to Jim Geiger [email protected]

Full time,