Application Guide

How to Apply for Engineering Manager, Data & Machine Learning

at Overstory

🏢 About Overstory

Overstory uniquely combines real-time satellite data with AI to directly combat climate change by reducing wildfire risks and improving electrical grid reliability. Their mission-driven team of diverse professionals across 15 nationalities is united by a passion for using technology as a force for good, making it an ideal workplace for those seeking meaningful impact in the climate tech space.

About This Role

As Engineering Manager for Data & Machine Learning at Overstory, you'll lead teams developing AI systems that analyze satellite imagery to identify vegetation risks to power lines, directly preventing wildfires and outages. This role involves managing technical strategy and execution for critical ML/data workflows that enable utilities to build a safer, more resilient grid.

💡 A Day in the Life

A typical day involves reviewing vegetation risk model performance with data scientists, prioritizing engineering tasks based on utility partner needs, and collaborating with cross-functional teams to ensure ML insights translate into actionable grid resilience recommendations. You'll balance technical leadership on satellite data pipelines with strategic planning for scaling Overstory's AI solutions to new regions.

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🎯 Who Overstory Is Looking For

  • Has 8+ years building ML/data systems with 3+ years managing ML/data teams in a high-growth startup environment
  • Possesses deep technical expertise in Python-based ML workflows and data systems to effectively guide data scientists and challenge technical decisions
  • Demonstrates experience collaborating closely with data scientists to translate satellite imagery analysis into actionable risk insights for utilities
  • Shows genuine passion for climate action and applying technology to solve complex environmental challenges like wildfire prevention

📝 Tips for Applying to Overstory

1

Highlight specific experience with satellite imagery, geospatial data, or remote sensing in your ML/data projects

2

Quantify your impact in previous startup/scale-up environments, especially how you've scaled ML systems during rapid growth

3

Demonstrate your understanding of the utility industry's vegetation management challenges and how AI can address them

4

Showcase experience with end-to-end ML workflows that move from data ingestion to actionable business insights

5

Emphasize your ability to bridge technical ML work with real-world climate impact, not just theoretical models

✉️ What to Emphasize in Your Cover Letter

["Your specific experience managing ML teams in high-growth environments and how you've scaled technical systems", "Examples of how you've applied ML/data systems to solve tangible, real-world problems (especially environmental or infrastructure challenges)", "Your passion for Overstory's mission to combat climate change through grid resilience and wildfire prevention", 'How your technical depth in ML/data systems enables you to guide teams working with satellite imagery and utility data']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Overstory's specific AI methodology for vegetation risk detection from satellite imagery (review their blog and technical content)
  • → The current challenges utilities face with vegetation management and wildfire prevention in different US regions
  • → Overstory's existing utility partners and how their solutions are deployed in real-world scenarios
  • → Recent climate/weather trends affecting grid reliability and how satellite data can provide early warning systems

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How you've managed ML teams through technical challenges in previous startup/scale-up environments
2 Your approach to prioritizing vegetation risk models when working with limited satellite data or computational resources
3 Experience with geospatial data pipelines and satellite imagery processing for ML applications
4 How you would collaborate with utility partners to translate their vegetation management needs into ML system requirements
5 Strategies for maintaining model accuracy and reliability as Overstory scales to new geographic regions and utility clients
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⚠️ Common Mistakes to Avoid

  • Focusing only on theoretical ML expertise without demonstrating practical application to real-world problems
  • Failing to show understanding of the utility industry's specific challenges with vegetation management and grid resilience
  • Presenting generic management experience without specific examples of leading ML/data teams in resource-constrained startup environments

📅 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:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Overstory!

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