Staff Data Scientist – Wildfire

Overstory

Staff Data Scientist leading wildfire fuel-detection research for Overstory’s AI and satellite-imagery platform. Validating models that help utilities prevent outages and reduce wildfire risk.

Posted 8/17/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in remote sensing, geospatial analysis, and machine learning to assess wildfire risk and vegetation structure. Proven ability to communicate complex research findings effectively to diverse audiences while mentoring teams in scientific methodologies.

Highest-signal resume keywords

Remote Sensing ExpertiseGeospatial AnalysisMachine Learning in PythonStatistical ModelingValidation Study Design

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Applied ResearchData ScienceStatistical ModelingMachine LearningGeospatial Analysis

Soft Skills

Excellent Communication SkillsMentoring

Tools & Technologies

GeoPandasScikit-learnPyTorchXGBoost

Industry Keywords

Wildfire ScienceFire EcologyForestryRemote SensingAtmospheric Science

Tech Stack

Tools & technologies

PythonPyTorchRemote SensingScikit-Learn

About the role

Key responsibilities & impact

Lead research into estimating vegetation structure, fuel conditions, and wildfire risk from satellite, LiDAR, and environmental data across diverse geographies
Design validation and evaluation methodologies, including ground-truth strategies, uncertainty quantification, and real-world-impact error analysis
Prototype and refine machine-learning modeling approaches and partner with ML engineers to translate them into production systems
Integrate fire science, fuel models, and fire behavior frameworks with data-driven methods
Define scientific standards for experimentation, reproducibility, and model interpretability
Communicate research findings to engineers, product teams, customers, and the wildfire science community
Mentor ML engineers on scientific methodology and domain reasoning

Requirements

What you’ll need

8+ years of applied research or data science experience in wildfire science, fire ecology, forestry, remote sensing, atmospheric science, or a related quantitative field
Deep expertise in remote sensing and geospatial analysis
Experience working with satellite imagery and large-scale environmental datasets
Strong statistical modeling and machine learning skills in Python
Proficiency with tools such as GeoPandas, scikit-learn, PyTorch, or XGBoost
Track record designing validation studies and evaluation frameworks for environmental or geospatial models
Excellent communication skills for technical and non-technical audiences
North America time zone availability: NST, AST, EST, CST, MST, or PST
Candidates must be living and working in one of the eligible countries listed by the company

Benefits

Comp & perks

Competitive, location-specific compensation and benefits
Flexible, autonomous and collaborative working environment rooted in trust
Home office stipend
Co-working budget
Ongoing education budgets
Annual in-person team gathering event
Option to occasionally meet up for in-person collaboration
Mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve the climate crisis