How to apply for Staff Product Manager, Machine Learning

About Overstory

Overstory uses real-time satellite data and machine learning to help utilities reduce wildfire risk and improve grid reliability, directly combating climate change. The company's focus on vegetation intelligence is both technically challenging and socially impactful, making it a unique place for mission-driven product leaders.

About the role

As Staff Product Manager for Machine Learning, you will own the roadmap for Vegetation Intelligence, driving ML models from detection to integration into risk models. You'll shift the product from being technically-led to customer-driven, ensuring that cutting-edge ML solves real utility problems and reduces wildfire threats.

A typical day

A typical day might start with a standup with ML engineers to review model performance metrics, then a user research session with a utility customer to understand their vegetation management pain points. Afternoon could involve refining the product roadmap with cross-functional stakeholders and writing specs for a new feature that integrates detection outputs into risk models.

Who Overstory is looking for

• 8+ years of PM experience with a strong track record of shipping ML-powered products end-to-end.
• Hands-on ability to discuss model performance, metrics, and trade-offs with data scientists and ML engineers.
• Proven experience turning a technically-focused roadmap into a customer-driven one, including conducting user research.
• Thrives in a fast-paced startup environment, comfortable with B2B products and building cross-functional consensus.

Tips for this application

• 1. Highlight specific ML products you've shipped, including how you balanced model accuracy with customer needs.
• 2. Show evidence of user research you've conducted and how it changed product priorities.
• 3. Tailor your resume to emphasize B2B and startup experience, especially with utilities or climate tech.
• 4. In your cover letter, explain why you care about wildfire risk and grid reliability.
• 5. Prepare to discuss trade-offs between technical rigor and customer-driven features in your past work.

What to cover in your cover letter

['Your passion for using ML to solve climate and wildfire challenges.', 'Concrete examples of shifting a product from technical-led to customer-driven.', 'Your ability to work closely with ML engineers and data scientists to improve model performance.', 'Your experience in fast-paced startups and B2B product strategy.']

Research before applying

• 1. Understand Overstory's current product offerings and how they use satellite data for vegetation management.
• 2. Read about the utility industry's wildfire mitigation strategies and regulations (e.g., California's SB 901).
• 3. Look at Overstory's blog or press releases for recent case studies or product announcements.
• 4. Familiarize yourself with competitors like Descartes Labs or Planet Labs, and identify Overstory's differentiation.

Likely interview topics

Based on the job description, expect questions about:

• 1. How would you prioritize between improving model accuracy vs. adding new customer-facing features?
• 2. Describe a time you used user research to change a product roadmap. What was the outcome?
• 3. How do you evaluate the business impact of an ML model? Walk through your framework.
• 4. How would you build consensus among engineering, data science, and sales on a contentious product decision?
• 5. What metrics would you use to measure success for Vegetation Intelligence products?

Common mistakes to avoid

• 1. Focusing only on technical ML details without connecting them to customer value or business outcomes.
• 2. Ignoring the mission-driven aspect—don't just talk about product management, show genuine interest in climate impact.
• 3. Providing generic PM examples that don't demonstrate experience with ML products or B2B user research.