This session will cover how data science is being deployed at Avista for scoring the risk of specific assets and specific section of the grid relative the risk of wildfire starts. Avista is deploying a data-science solution to uniquely score wildfire risk based on a combination of grid attributes at specifics locations (vegetation, weather, location, asset, etc.) for a total of hundreds of risk inputs at a sub-feeder level granularity. This will be a combination presentation led by Dave James of Avista supported by Tom Martin of TROVE Predictive Data Science.