Staff Data Scientist (Wildfire)

Location: Remote; candidates must be living and working in the United States, the Netherlands, the United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark, or Canada. Working hours must align with North American time zones: NST, AST, EST, CST, MST, or PST.

Company

hirify.global uses AI, satellite imagery, and environmental data to help utilities identify vegetation risks, prevent outages, reduce wildfire risks, and build a more resilient electrical grid.

What you will do

• Lead research on estimating vegetation structure, fuel conditions, and wildfire risk from satellite, LiDAR, and environmental data.
• Design validation and evaluation methods, including ground-truth strategies, uncertainty quantification, and real-world error analysis.
• Prototype and refine machine learning models and partner with ML engineers to bring them into production.
• Integrate fire science, fuel models, and fire behavior frameworks with data-driven methods.
• Define standards for experimentation, reproducibility, and model interpretability.
• Communicate research findings to engineers, product teams, customers, and the wildfire science community while mentoring ML engineers.

Requirements

• 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 using satellite imagery and large-scale environmental datasets.
• Strong statistical modeling and machine learning skills in Python.
• Experience with tools such as GeoPandas, scikit-learn, PyTorch, or XGBoost.
• Experience designing validation studies and evaluation frameworks for environmental or geospatial models.
• Excellent communication skills for explaining complex scientific work to technical and non-technical audiences.

Nice to have

• Familiarity with fire behavior or fuels modeling frameworks, including Rothermel-based models or LANDFIRE fuel classifications.
• Experience integrating physics-based models with ML, active learning, or uncertainty quantification.
• Peer-reviewed publications in wildfire science, remote sensing, or environmental modeling.
• Familiarity with GCP, Vertex AI, or similar cloud platforms.
• Experience working in a remote-first or globally distributed team.

Culture & Benefits

• Flexible, autonomous, and collaborative remote working environment.
• Location-specific compensation and benefits.
• Home office stipend, co-working support, and ongoing education budgets.
• Annual in-person team gathering with optional in-person collaboration meetups.
• Mission-driven work focused on reducing wildfires, protecting natural resources, and addressing the climate crisis.