Delivering product strategy and development for Coinbase's Transaction Monitoring System (TMS), driving innovation in fraud prevention and risk management through advanced analytics and machine learning. Responsible for enhancing detection capabilities, reducing operational overhead, and delivering measurable business impact across cross-functional teams.

Led analytics to enhance fraud detection, boosting model performance by 7% through pattern analysis and feature expansion. Managed a team of 5 to improve alert efficiency by 71% via process redesign. Used SQL, Python, and R for time series and cluster analysis, driving 5–15% gains in alert quality. Built dashboards in Spotfire/Tableau and partnered with cross-functional teams to translate insights into action.

Transformed structured and unstructured financial data using SQL and SSIS to support suspicious activity monitoring. Conducted large-scale data mining across millions of transactions, uncovering behavioral patterns that improved monitoring system accuracy by 21%.

Led a global team supporting vendor management across pricing and rates, managing and resolving ~800 weekly notices. Investigated securities data using MSSQL, Oracle, and Tableau to identify patterns and root causes, driving issue resolution and process improvements.