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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Geospatial Statistician for Extreme Weather and Model Evaluation (Academic Hourly) - **Company:** University of Illinois - **Location:** Urbana, IL, United States - **Salary:** $41,600.0 - $52,000.0 - **Contract:** Contract - **Skills:** Geographic Information Systems, ArcGIS (Software), Computer Programming, Data Transformation, Data Visualization, R (Programming Language), Python (Programming Language), MATLAB, NetCDF, Quantum GIS (QGIS), Data Ingestion, Model Validation - **Published:** May 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=096994860dc5e839 ## About the Role Do you have experience in Statistics research?, 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., * Background in statistics, geospatial data science, atmospheric sciences, environmental data science, remote sensing, engineering, or a related field. * Experience working with large-scale environmental, weather, climate, or geospatial datasets. * Strong programming skills in Python, R, MATLAB, or similar languages. * Familiarity with statistical modeling, spatial analysis, uncertainty analysis, or model evaluation methods. KNOWLEDGE SKILLS AND ABILITIES * Experience working with gridded model outputs and point-based observational datasets. * Working knowledge of environmental and weather data sources, such as in-situ observations, radar, satellite products, reanalysis datasets, or numerical weather prediction model outputs. * Familiarity with geospatial data tools, packages, and formats, such as NetCDF, GeoTIFF, shapefiles, GeoJSON, xarray, rasterio, geopandas, ArcGIS, or QGIS. * Experience with spatial matching, interpolation, aggregation, bias correction, validation, or uncertainty quantification across model and observation datasets. * Understanding of atmospheric processes, weather systems, or extreme weather events. * Experience with automated workflows, data visualization, dashboards, or operational forecasting systems. ## Description * 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. 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