IRS Project, Quick Response Team• Fraud Detection Enhancements: Designed and implemented business rules to identify fraudulent and identity theft tax returns, improving detection accuracy and saving the IRS millions of dollars annually.• Lead Analysis and Data Collection: Gathered and analyzed leads from top executives regarding emerging fraud schemes using SQL and Python, facilitating informed decision-making and enhanced response strategies.• Stakeholder Communication: Developed data-driven presentations to communicate findings and insights to stakeholders, integrating their feedback to improve report effectiveness and clarity.• Data Presentation and Reporting: Compiled and presented comprehensive data stories to stakeholders, incorporating their feedback to refine and enhance the clarity and impact of the reports.• Ongoing Monitoring and Reporting: Produced and maintained daily and weekly reports on suspicious activities, including anomalies in emails, bank accounts, and year-over-year discrepancies in tax returns.• Code Debugging and Optimization: Rewrote and optimized legacy code from previous team members to improve performance and data quality, addressing and resolving issues efficiently.Opioid Task Force• ETL Process Development: Created and maintained ETL processes using Python and Talend to integrate open-source data from various sources, including Census, Bureau of Labor Statistics, and NIBRS, ensuring data quality and accessibility.• Data Sharing and Collaboration: Collaborated with Emergency Medical Services and the Department of Criminal Justice to securely share sensitive data, supporting public safety initiatives.• Data Pipeline Management: Managed data pipelines utilizing API, FTP, and S3 to ensure reliable data flow and accessibility for analytical purposes.• Award-Winning Dashboard Development: Contributed to a dashboard project recognized by the governor for its excellence in public safety.

· Ran weekly and monthly reports, collecting data from multiple teams to support business operations.· Conducted backend data cleaning and preprocessing to standardize data formats and improve data quality.· Ensured data privacy by implementing masking techniques for personally identifiable information (PII).· Diagnosed and optimized Python and SQL scripts for efficiency and performance, ensuring optimal data processing and analysis.