Staff Data Scientist - Wildfire

Responsibilities

Lead the scientific foundation of fuel detection models by translating satellite and environmental data into wildfire risk insights. Design rigorous validation methodologies and partner with ML engineers to integrate fire science frameworks into production systems.

Requirements

Requires 8+ years of applied research experience in wildfire science, remote sensing, or a related quantitative field. Candidates must possess strong Python programming skills and expertise in geospatial analysis and statistical modeling.

Skills

• Wildfire science
• Remote sensing
• Geospatial analysis
• Python
• Machine learning
• Statistical modeling
• Satellite imagery
• LiDAR
• Environmental data
• GeoPandas
• Scikit-learn
• PyTorch
• XGBoost
• Data science
• Fire ecology
• Forestry

Benefits

• Competitive compensation
• Flexible working environment
• Home office stipend
• Co-working budget
• Ongoing education budget

About this role

Role & Team
We are excited to add a Staff Data Scientist, Wildfire to our team. This individual will lead the scientific foundation of our Fuel Detection Model, the core engine that translates satellite and environmental data into an understanding of vegetation structure, fuel loads, and wildfire risk.

Working alongside ML engineers, and a product team, you'll define accuracy for our models, design the research and validation methods that prove it, and ensure our modeling choices are grounded in fire science and remote sensing fundamentals. This is a great opportunity for someone who is energized by open scientific questions with direct real-world stakes, and who wants their research to shape how utilities prevent catastrophic wildfires.
Time Zone Requirement: North America (NST, AST, EST, CST, MST, PST)
What You’ll Do
Lead research into how vegetation structure, fuel conditions, and wildfire risk can be estimated from satellite, LiDAR, and environmental data across diverse geographies
Design rigorous validation and evaluation methodologies, including ground-truth strategies, uncertainty quantification, and error analysis tied to real-world impact
Prototype and refine ML modeling approaches, then partner with ML engineers to translate them into production systems
Integrate established fire science, such as fuel models and fire behavior frameworks, with data-driven methods
Define scientific standards for experimentation, reproducibility, and model interpretability across the modeling organization
Communicate research findings clearly to engineers, product teams, customers, and the broader wildfire science community
Mentor ML engineers on scientific methodology and domain reasoning
Skills & Experience
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, including working with satellite imagery and large-scale environmental datasets
Strong statistical modeling and machine learning skills in Python, with tools like GeoPandas, scikit-learn, PyTorch, or XGBoost
Track record of designing validation studies and evaluation frameworks for environmental or geospatial models
Excellent communication skills, with the ability to make complex scientific work legible across technical and non-technical audience
Nice To Have
Familiarity with fire behavior or fuels modeling frameworks (e.g., Rothermel-based models, LANDFIRE fuel classifications)
Experience integrating physics-based models with ML, or with active learning and uncertainty quantification
Peer-reviewed publications in wildfire science, remote sensing, or environmental modeling
Familiarity with GCP, Vertex AI, or similar cloud-based platforms
Experience in remote-first or globally distributed team
Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.
What We Offer
Competitive, location-specific compensation and benefits
Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
Home office stipend, co-working and ongoing education budgets
A company culture that genuinely embodies each of our core values
To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis