Remote Wildland Fire Risk Scientist | GIS & ML

Innovate!, Inc.; United States; Remote; USD 90,000 - 97,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401K with match

Life Insurance

PTO

Job summary

Innovate! Inc.

seeks a Wildland Fire Risk Scientist to provide advanced scientific and geospatial research support focused on wildfire exposure and risk to buildings, the wildland-urban interface (WUI), and other valued assets. The role will apply remote sensing, GIS, geospatial processing, scripting, statistical analysis, simulation modeling, machine learning, and science communication to support national-scale wildfire risk assessment and mitigation research.

Qualifications

• PhD, advanced degree, or equivalent experience in ecology, landscape ecology, forestry, fire science, or related field.
• Minimum 3–5 years of related work in fire ecology.
• Advanced understanding of fuel types and wildland fire behavior.
• Experience with GIS software and image processing.
• Proficiency in Python and R for analyses and modeling.

Responsibilities

• Advance wildfire exposure and risk research for buildings and WUI at national scales.
• Develop models using simulation, deep learning, and machine learning for exposure and damage.
• Lead journal publications in wildfire risk research.
• Build and maintain datasets on annual building losses due to wildfires.
• Create prototypes and identify data sources for critical assets impacted by wildfires.
• Develop, update, and analyze global and national Wildland Urban Interface datasets.

Skills

Fire ecology

Python & R

GIS analysis

Technical writing

Collaboration

Machine learning

Education

PhD or equivalent experience

Tools

ERDAS

ArcGIS/ArcGIS Pro

QGIS

Job description

Innovate! Inc.

seeks a Wildland Fire Risk Scientist to provide advanced scientific and geospatial research support focused on wildfire exposure and risk to buildings, the wildland-urban interface (WUI), and other valued assets. The role will apply remote sensing, GIS, geospatial processing, scripting, statistical analysis, simulation modeling, machine learning, and science communication to support national-scale wildfire risk assessment and mitigation research.