I led the end-to-end UX for IBM’s Synthetic Data Generator, a visual tool that enables users to create privacy-safe, AI-ready tabular datasets using differential privacy and simulation-based methods. I collaborated with PMs, engineers, data scientists, and content strategists to design workflows from incubation to GA, including launching on AWS and integrating into watsonx. Our design contributed to a $7M PoC win and helped make synthetic data generation a core offering. Full case study available upon request.