Job Responsibilities:

• Research and implement ideas for improving trade scheduling, order placement and order routing models used by various equity trading algorithms
• Research and implement new algorithms/approaches such as machine learning for optimal trade execution and order routing
• Perform analysis of large data sets comprising of market data, orders, executions to understand algorithm performance and develop signals and analytics to improve performance
• Enhance the model development and simulation frameworks
• Implement client and desk requests for bespoke algorithms. Support client inquiries and assist with performance analysis and reporting

Qualifications:

• Good understanding of US equity trading and market microstructure
• Knowledge of algorithmic trading (order books, volume forecasting, equity impact cost models etc.)
• Minimum 2 years of experience in trading environment and in developing execution algorithms, or high frequency trading strategies
• Experience in applying statistical modelling and machine learning towards analysis of large data sets
• Strong analytical and quantitative skills and experience using statistical programming languages such as R or Python
• Object oriented programming (Java, C++)
• Experience with Q/KDB or time series tick databases desirable
• Good communication skills, both verbal and written. This role will require interaction with clients and contributing to white papers
• Ability to juggle multiple tasks and projects in a fast-paced work environment
• Demonstrate an appreciation of a diverse workforce. Appreciates differences in style or perspective and uses differences to add value to decisions or actions and organizational success
• PhD or Masters in Mathematics, Physics, Finance, Statistics, Computer Science preferred