Ádám Váradi

I’m a Data Scientist with 5+ years in data operations, BI, and analytics engineering, specializing in Python, SQL, machine learning, and cloud reporting workflows. I’ve delivered end-to-end work from predictive feature engineering to model evaluation and production reporting, including a reproductive health ML proof-of-concept.

I recently developed an XGBoost-based health classification model achieving 76% weighted F1 on real-world validation data. I also engineered synthetic menstrual cycle datasets from clinical literature and built interactive Looker Studio dashboards backed by BigQuery SQL, plus automated weekly pipelines to monitor usage, scan errors, and stock utilization.

Earlier, I integrated and maintained analytics and monitoring systems for real-time data pipelines, improving deployment efficiency by replacing outdated components. I also led operational frameworks as a founding support team member for MemSQL (SingleStore), designing alerting/monitoring for early fault detection and serving as Tech Lead, while supporting ISO 9001 process improvements and cybersecurity resilience.