Analyze transaction enrichment product performance, data quality, accuracy, match rates, and other metrics. Investigate anomalies in large datasets, build dashboards and automated alerts, improve QA processes and workflows, and develop documentation and monitoring standards. Partner with Product, Engineering, and AI/ML Data Science teams to translate insights into product improvements and automate recurring analytical work.