Senior Data Scientist / Machine Learning Engineer at MLOps

Led development of ML pipelines and advanced analytics for decision intelligence, predictive forecasting, and anomaly detection across government and enterprise programs. Built end-to-end ML pipelines with Python, PyTorch, XGBoost, Spark, and Airflow; deployed models as containerized services on Docker and Kubernetes with real-time and batch inference; established model monitoring and governance; partnered with cross-functional teams to translate mission requirements into deployable analytics.

Led development of end-to-end ML pipelines, predictive analytics, anomaly detection, and forecasting solutions; designed scalable ML workflows and governance across government and enterprise programs; deployed ML models using Docker and Kubernetes; built data-powered decision support across cloud platforms; established monitoring, explainability, and stakeholder collaboration.

Data Scientist at Johnson & Johnson

Developed and deployed data science and ML solutions supporting pharmaceutical manufacturing, supply chain optimization, quality analytics across regulated business units.

Machine Learning Engineer at Facebook

Developed and productionized ML models supporting news feed ranking, content recommendations, growth experiments, and integrity signals across Facebook's consumer platform.