Application Guide
How to Apply for Solutions Engineer
at Overstory
🏢 About Overstory
Overstory uses real-time satellite data to help utilities reduce wildfire risk and improve grid reliability, directly combating climate change. Their focus on actionable insights from geospatial data makes them a unique player at the intersection of climate tech and energy infrastructure. Working here means contributing to a mission-driven team that's transforming how power grids are monitored and maintained.
About This Role
As a Solutions Engineer, you'll own customer projects end-to-end, from data requests to final analysis, working closely with Customer Success. You'll process large geospatial datasets, identify patterns for productization, and partner with product and engineering to build the roadmap. This role is impactful because you'll directly turn satellite data into actions that protect communities and critical infrastructure.
💡 A Day in the Life
A typical day might start with a standup with Customer Success to review active projects, then dive into a Jupyter notebook to process a new satellite image tile and validate it against utility data. After lunch, you might present findings to a customer, then collaborate with product on standardizing a common analysis into a reusable pipeline. You'd end the day updating GitHub repos and documenting workflows for the team.
🚀 Application Tools
🎯 Who Overstory Is Looking For
- Has 2-4 years of professional experience with large geospatial datasets (vector and raster) in a customer-facing role, such as a geospatial analyst or solutions engineer.
- Is proficient in Python, Jupyter, git/GitHub, and command-line workflows, with a track record of building analytical pipelines.
- Thrives on managing multiple projects simultaneously and can balance technical depth with clear communication to non-technical stakeholders.
- Is passionate about climate change and eager to apply geospatial skills to reduce wildfire risk and improve grid reliability.
📝 Tips for Applying to Overstory
Tailor your resume to highlight specific geospatial projects where you processed and analyzed large datasets (e.g., satellite imagery, LiDAR, or utility data) and delivered customer-ready outputs.
In your cover letter, explicitly mention your Python stack experience (Jupyter, git) and give an example of how you turned a one-off analysis into a repeatable product.
Showcase your ability to communicate technical findings to non-technical audiences—consider including a sample output or visualization from a past project.
Research Overstory's blog or case studies to understand their current product offerings and mention how your skills could accelerate their productization roadmap.
Address the remote aspect: demonstrate self-motivation and async communication skills, as the role is remote (US) and requires close collaboration with Customer Success.
✉️ What to Emphasize in Your Cover Letter
["Emphasize your experience with large geospatial datasets in a customer-facing capacity, and how you've translated technical results into actionable insights.", 'Highlight your Python and Jupyter proficiency, and describe a project where you processed raster/vector data end-to-end.', "Show enthusiasm for Overstory's mission: reducing wildfire risk and improving grid reliability through satellite data.", 'Mention your ability to identify patterns and standardize workflows, aligning with their goal of productizing one-off projects.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Read Overstory's blog posts and case studies to understand their current products and customer success stories.
- → Familiarize yourself with the basics of wildfire risk modeling and utility vegetation management—key context for the role.
- → Look up their engineering blog or GitHub to see their tech stack and open-source contributions.
- → Check recent news about Overstory's partnerships or funding to understand their growth trajectory.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Don't apply without demonstrating specific geospatial data experience—generic data science or software engineering backgrounds may not fit.
- Avoid vague descriptions of Python skills; be ready to discuss specific libraries (e.g., rasterio, geopandas, xarray) and workflows.
- Don't neglect the customer-facing aspect—focusing only on technical skills without showing communication and relationship-building ability is a miss.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!