Wildland Fire Risk Scientist

KBR•Sioux Falls, SD

23h

About The Position

The primary focus of this position is to provide research support to the USGS team tasked with understanding wildfire risk to buildings, the wildland-urban interface, and other valued assets. This will require advanced level science support with experience in remote sensing, geographic information systems, geospatial processing, scripting, statistical analysis, and science communications.

Requirements

Must have a 3-year residency in the United States
This position requires the ability to obtain and maintain a national agency check and background investigation after hire to obtain credentials for facility access and user accounts.
PhD or advanced Degree or equivalent experience in ecology, landscape ecology, forestry, fire science, conservation science or another relevant field - especially study in how ecological systems function both naturally and after disturbance
Must have minimum 3-5 years of recent and related work experience in fire ecology and knowledge with plant community dynamics across the landscape
Advanced understanding of ground, surface, and canopy fuel types/characteristics and their effects on wildland fire behavior in conjunction with environmental factors
Experience with image processing and GIS software (e.g., ERDAS, ArcGIS, ArcPro, QGIS)
Familiarity with raster and vector data processing and ability to perform spatial analysis and validation
Strong interpersonal communication, technical writing, editing and presentation skills and an advanced knowledge of Microsoft office tools for reporting and documentation of processes and procedures
Experience with Python and R, and potentially AI-supported development environments (e.g., Kiro) to develop models, data analyses, and visualizations
Experience with shared code repositories
Ability to serve in both lead author and co-author roles to plan and complete manuscripts targeting high-impact scientific journals

Nice To Haves

Ability to self-teach in areas of weakness utilizing available on-the-job training resources

Responsibilities

Forward research in wildfire exposure and risk to buildings, the wildland-urban interface (WUI), and other valued assets to inform DOI and USWFS wildfire risk assessments and risk mitigation strategies.
Advance methods to predict wildfire exposure and damage to buildings at national or larger scales using simulation models and deep and machine learning
Lead development and publication of journal articles related to this research
Develop, maintain, and expand data sets that quantify building losses caused wildfires annually
Develop prototypes and identify data sources for non-building valued assets such as communication, energy, hydrological, or transportation infrastructure impacted by wildfires
Develop, update, and analyze global- and national-scale datasets mapping Wildland Urban Interface using building footprints, census bureau, land cover, and fire occurrence data
Ability to contribute to the definition, direction, and implementation of the Wildland Fuels Program at EROS
Participate in virtual and occasional in-person team meetings as needed
Ability to work in a team environment to help shape, manage and execute projects applying geospatial data and systems to solve geospatial problems