Selected Anti-Money Laundering Matter:- Created data pipelines to periodically extract and transform transactional data from Client Bank’s Oracle data warehouse, load to SQL Server, and refresh key analytics dashboards- Generated social network graphs using Python NetworkX to identify patterns of activity between related entities involved in a $350 million money laundering scheme- Designed SQL tests to verify the accuracy of Client Bank’s automated suspicious activity monitoring rules and provided recommendations for improvements to the automated monitoring processOther Roles and Responsibilities:- Provide training to junior team members in introductory SQL, data management best practices, and effective quality control strategies- Cross-collaborate with other practices, including Corporate Finance and Risk & Investigations, to provide effective custom data solutions meeting their project needs- Work closely with client-side data admin teams to identify and extract key data sources while maintaining the security and integrity of highly sensitive data- Regularly update project managers with accurate forecasts of time requirements and anticipated obstacles throughout the lifecycle of a matter

Selected Remediation Matter:- Automated the calculation of market performance to back-calculate earnings for over 10,000 retirement accounts that had been misallocated over a three year period, determining financial damages owed per account due to misallocation- Wrote SQL procedures to transform customer transactions from Client’s database into structured inputs to a Python program which referenced historical daily market price and dividend data to calculate portfolio value over time- Took ownership of writing Python modules to process specific transaction types, utilizing Gitlab to seamlessly integrate modules written by other team members