Andrea joined PG&E more than 4 years ago as the first hire dedicated to developing wildfire risk planning models. Andrea contributed to scaling the team in addition to developing, releasing, and operationalizing 3 iterations of the risk planning models. She developed the framework for asset-based ML models to predict the likelihood of equipment failure that could lead to a catastrophic wildfire. Now, Andrea manages the Electric System Predictive Analytics team within the Wildfire Emergency Operations organization to proactively predict system failures, assess effectiveness of mitigations, and engage with planning stakeholders to operationalize and improve the risk models.

Prior to PG&E, Andrea spent 2 years as a Data Scientist at a B2B software startup focused on industrial facilities. Before switching careers to data science, she worked as a licensed civil engineer in each phase of the engineering lifecycle: planning, design, and construction. Andrea holds a BS in Civil Engineering from UCLA and an MS in Civil Engineering from Tufts University.