Kayla Smith

As a Senior Research Analyst at Dun & Bradstreet, I leverage my expertise in Python scripting and Excel automation to analyze large datasets, focusing on fraud detection and trend analysis. My role involves creating dynamic visualizations and fraud ring charts that support investigative teams in identifying suspicious account behaviors. I thrive in collaborative environments, working with cross-functional teams to implement process improvements based on analytical findings.

Previously, I served as a Fraud Analyst at TaskUs, where I investigated fraudulent purchasing activities and identity theft. My responsibilities included monitoring high-risk transactions and providing intelligence reports to management. I also conducted private investigations, compiling detailed reports for law enforcement. Currently, I am expanding my skill set as an AI Training Specialist, where I provide coding expertise to improve AI model outputs and contribute to training datasets.