Wildland Fire Risk Scientist: National-Scale Risk & ML

KBR, Inc.; Sioux Falls (SD); On-site; USD 90,000 - 130,000; Full time

Job summary

KBR in Sioux Falls, SD seeks a Wildland Fire Risk Scientist to support USGS wildfire risk assessments. You will apply GIS, remote sensing, and data-driven methods to analyze risk to buildings and the wildland-urban interface.

The role emphasizes advanced scripting in Python/R, manuscript authorship, data table development, and collaboration with a multidisciplinary team to map and mitigate wildfire impacts at national scales.

Qualifications

• PhD or advanced degree in ecology, landscape ecology, forestry, fire science, conservation science or related field.
• 3–5 years of recent and related work experience in fire ecology and landscape dynamics.
• Advanced understanding of ground, surface, and canopy fuel types and their effects on wildland fire behavior.

Responsibilities

• Forward research in wildfire exposure and risk to buildings and the wildland-urban interface to inform risk assessments and mitigation strategies.
• Advance methods to predict wildfire exposure and damage at national or larger scales using models and ML/DL approaches.
• Lead development and publication of journal articles related to this research.
• Develop, maintain, and expand datasets that quantify building losses caused by wildfires annually.
• Develop prototypes and identify data sources for non-building assets impacted by wildfires.
• Develop, update, and analyze global- and national-scale datasets mapping Wildland Urban Interface using building footprints, census data, land cover, and fire data.

Skills

Python and R

GIS and remote sensing

Technical writing

Interpersonal communication

Presentation skills

Education

PhD in ecology/landscape ecology/forestry/fire science or related field

Tools

ERDAS

ArcGIS

ArcPro

QGIS

Git

Job description

KBR in Sioux Falls, SD seeks a Wildland Fire Risk Scientist to support USGS wildfire risk assessments. You will apply GIS, remote sensing, and data-driven methods to analyze risk to buildings and the wildland-urban interface.

The role emphasizes advanced scripting in Python/R, manuscript authorship, data table development, and collaboration with a multidisciplinary team to map and mitigate wildfire impacts at national scales.