How to apply for Staff Data Scientist - Wildfire

About Overstory

Overstory uses AI and satellite imagery to find vegetation risks near power lines before they cause wildfires or outages. The company works with utility partners across the Americas to support grid reliability. The team is remote across the Americas and Europe and focuses on climate action through technology.

About the role

As a staff data scientist on the wildfire team, you will build models that turn satellite data into vegetation risk assessments for utilities. Your work directly supports wildfire prevention and grid reliability. This is a senior individual contributor role on a remote US team.

A typical day

A typical day might involve reviewing satellite imagery pipelines, training or evaluating a risk model, and meeting with engineers or product managers to align on how the model output will be used. You may also spend time investigating data quality issues or writing documentation for utility-facing risk scores. Since the team is remote and distributed, much of the collaboration happens over video calls and written updates.

Who Overstory is looking for

• Has senior or staff-level experience building production machine learning models, ideally with geospatial or satellite imagery data.
• Can translate messy real-world data (vegetation, infrastructure, weather) into risk scores that utility partners can act on.
• Is comfortable working remotely with a distributed team across time zones.
• Has domain interest or experience in climate, energy, utilities, or wildfire risk.

Tips for this application

• Read Overstory's published materials or blog posts about how they detect vegetation risk with satellite imagery, and reference a specific method or product in your application.
• In your resume, quantify model impact: accuracy, latency, scale of data processed, or number of assets scored.
• Name the specific satellite or remote sensing datasets you have worked with (e.g., Sentinel, Landsat, Planet) if applicable.
• Explain why wildfire and grid reliability specifically interest you, not just climate tech in general.
• Check whether Overstory lists a separate careers email or application portal, and follow their instructions exactly rather than sending a generic resume.

What to cover in your cover letter

Describe a time you built a model that informed a real operational decision, especially with geospatial or sensor data. Explain how you would approach the problem of prioritizing vegetation risk across millions of assets. State why you want to work on wildfire and grid reliability specifically. Mention your experience working remotely or with distributed engineering teams.

Research before applying

• Overstory's product page and any case studies with utility partners to understand what output customers actually receive.
• The types of satellite imagery and AI methods Overstory mentions publicly, so you can speak to their technical stack.
• Recent news about wildfire risk and grid reliability in the US to understand the regulatory and operational context.
• Overstory's team page or LinkedIn to see who works on data science and what backgrounds they have.

Likely interview topics

Based on the job description, expect questions about:

• How would you design a model to prioritize vegetation risk from satellite imagery for a utility customer?
• Walk us through a production ML system you built end to end, including data pipelines, training, and deployment.
• How do you handle label noise or ground truth scarcity in geospatial data?
• How would you measure the business impact of a wildfire risk model for a utility partner?
• Describe a time you disagreed with a product or engineering decision and how you handled it.

Common mistakes to avoid

• Submitting a generic data science resume that does not mention geospatial, satellite, or remote sensing experience.
• Focusing only on model accuracy without explaining how the model would be used by a utility to make decisions.
• Ignoring the wildfire and grid reliability context and treating this as just another climate tech role.