Geospatial Statistician for Extreme Weather and Model Evaluation (Academic Hourly)

The DPI Climate Hub (https://www.climate-dpi.org) is seeking a highly motivated candidate with expertise in statistics, geospatial data analysis, environmental data science, atmospheric sciences, remote sensing, or a related field to support research and development for the AerisIQ weather forecasting system (https://aerisiq.io) The ideal candidate will contribute as an Extreme Weather and Geospatial Statistics Analyst, supporting the analysis of high-impact weather events and the evaluation of model performance against observational datasets. This role will focus on developing statistical and geospatial workflows to compare numerical weather model outputs with in-situ observations, radar, satellite, reanalysis, and other environmental datasets. The candidate will help translate model–observation insights into operational tools, performance metrics, and decision-support products. Key Responsibilities Conduct retrospective analyses of extreme weather events, including storms, high winds, heatwaves, extreme rainfall, and flooding. Perform quantitative comparisons between simulated forecasts and observational datasets across space and time. Develop statistical metrics and geospatial methods to evaluate model performance, bias, uncertainty, and event detection skill. Process and analyze large-scale gridded and point-based environmental datasets, including NWP outputs, station observations, radar, satellite, and reanalysis products. Support spatial matching, interpolation, aggregation, and validation workflows for model–observation comparison. Collaborate with software engineers and domain experts to develop automated workflows for data ingestion, preprocessing, post-processing, visualization, and analysis. Contribute to the development of operational evaluation tools and decision-support products for extreme weather applications.