Staff Product Manager, Machine Learning
About the role
Role & Team
You’ll lead a core part of our Vegetation Intelligence, the product area that turns remote sensing imagery and data into the vegetation insights that utilities act on every day, through world-class machine learning models. It’s one of Overstory’s most foundational products, live with customers now, and it sits at the center of how we prevent outages and stop wildfires. Every missed tree is an outage or a fire that could have been prevented.
The job is twofold. One is real ML-adjacent work: pushing our detection models further and turning their raw outputs into risk data precise enough for customers to trust and act on. You’ll need to be comfortable with complex machine learning models and geospatial data, close to the data science and engineering teams, and fluent enough in model trade-offs to make good calls with data scientists and ML engineers.
The other side is where you get to build new capabilities: taking that same data and pushing it into new products and capabilities customers don't have yet. You'll run user research, ground new product bets in the decisions customers make in the field, and turn a strong model into products that prevent real fires and real outages.
You’ll report to the Director of Product and own the strategy and roadmap for this product area end to end.
Time Zone Requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST, CST) Comfortable maintaining 3-4 hours of overlap European working hours for collaboration with the broader Overstory team.
What You'll Do
- Own the roadmap for Vegetation Intelligence, spanning from the ML models that produce our risk data to the products that turn it into customer action.
- Push our detection models further, and help fold their outputs into Overstory’s broader outage and ignition risk models.
- Contribute towards increasing the number of actionable insights: run user research, ground priorities in the operational decisions customers actually make, and make sure what we ship drives real action in the field.
- Shift the roadmap from scaling- and technical-led to customer-driven, without losing the technical rigor that got us here.
- Work closely with data scientists and ML engineers to turn model capability into shipped product value, an