A highly analytical role at the intersection of data science and trading. Daily work was based primarily in Python utilizing pandas and numpy statistical packages. Introduced the idea of leveraging Python's Machine Learning module SciKit-Learn, Random Forest algorithms to classify potential trades across large multi-dimension datasets. Completed trading associate training, option theory and volatility arbitrage.
• Placed in hybrid trading and technology role responsible for automation and building systematic trading workflows, heavy use of Python and SQL daily
• Initiated and led projects with development team to gather insights on large sets of financial data streams
• Created automated reports distributed firm wide on real-time data of option greeks, risk and PnL
• Introduced machine learning algorithms (random-forest) approach to classify potential trading opportunities
across real-time market data
• Created & managed databases and archived order flow to gain insights and trends utilizing Python and SQL
• SQL dialects used, PostgreSQL and Microsoft SQL Server