Spatial Wildfire Analyst

This is a fully remote position, open to applicants in Montana.

📋 Description

• Enhance the calibration and validation of fire modeling and potentially create innovative fuel and fire modeling techniques.

• Assist in the advancement of automation in fire behavior modeling.

• Conduct spatial and temporal data analysis across extensive landscapes.

• Design and implement frameworks for spatial data and modeling.

• Establish and comply with data standards.

• Integrate data quality assurance and control in all deliverables.

• Document methodologies and support the creation of reports, presentations, and other publications.

• Participate in developing proposals for new business ventures.

⛳️ Requirements

• Proven experience in designing and executing custom analyses of vector and raster outputs from various fire modeling systems.

• Experience in parameterizing, operating, and interpreting incident-level wildfire behavior modeling systems, including FSPro, FARSITE, and similar tools.

• Proficient in using commercial or open-source GIS software (e.g., ArcMap, ArcGIS, or QGIS) for spatial analysis of vector and raster datasets.

• Skilled in writing or modifying scripts for spatial analysis tasks.

• Ability to work effectively within a multi-disciplinary problem-solving team.

• Strong attention to detail.

• Quick learner with the ability to grasp new concepts rapidly.

• Exceptional oral and written communication abilities.

• Familiarity with Rothermel-based spatial fire behavior modeling systems, such as FSim, RANDIG, FConst, FSPro, or FlamMap.

• Understanding of how fire behavior modeling inputs—including surface and canopy fuel characteristics, weather/climate, and topography—impact fire behavior.

• Experience in producing and/or analyzing spatial fire modeling outputs, like burn probability, fire intensity, perimeter polygons, and ignition sources, including datasets available on the FS Research Data Archive.

• Familiarity with fuelscape vegetation and fuels datasets, including those generated by LANDFIRE’s vegetation and fuels teams. Examples include Existing Vegetation Type (EVT), Fuels Vegetation Cover (FVC), Canopy Cover (CC), Canopy Base Height (CBH), and Fuel Disturbance (FDist).

• Background in wildfire sciences and/or management, including incident response, fuels management, and fire research.

• Experience with Python geospatial libraries like GeoPandas, Rasterio, Shapely, GDAL, and ArcPy (or their R equivalents), with the capability to use existing Python scripts and contribute to the enhancement and automation of fire modeling.

• Knowledge of land management and wildfire decision support datasets, models, software, and workflows, such as LANDFIRE, Wildland Fire Decision Support System (WFDSS), FlamMap, Nexus, WindNinja, FSim, Interagency Fuel Treatment Decision Support System (IFTDSS), and Google Earth Engine.

• Familiarity with processing remote sensing datasets, including LiDAR, NAIP, and LANDSAT.

• Understanding of ecology in dry forests and Mediterranean environments, along with ecological forest management; capable of effectively conveying scientific concepts to non-expert audiences.

• Experience in supporting risk-based decision-making for wildfire incidents as part of a large-fire incident management team (e.g., LTAN, FBAN, etc.).

🏝️ Benefits

• Health insurance.

• Unlimited PTO policy.

• 401k.

• Company equity.

• One-time home office set-up allowance.