Overstory

Machine Learning Engineer

• 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, and define what “good” looks like for a model in production.
• Explore how feedback from customers and end users, like arborists, can improve model performance over time.
• Communicate clearly and often with the broader product and engineering team, so trade-offs, model limits, and priorities stay visible.
• Contribute to Overstory’s broader product strategy so Vegetation Insights supports where the rest of the product is headed

Staff Product Manager, Machine Learning

Product Marketing

• Own Overstory's core positioning and messaging, from category narrative to product-level value propositions.
• Shape the language that defines how utility leaders understand wildfire risk, vegetation-related risks, and the cost of inaction.
• Lead pricing, packaging, and GTM strategy for new and existing products, including custom deals with complex, multi-stakeholder buying dynamics.
• Build the sales enablement materials (battlecards, pitch narratives, ROI models) that support a sales team navigating long cycles across vegetation managers, engineers, and C-suite. Train reps on how to use them and stay close enough to deals to know when they're not working.
• Partner with product and sales leadership on go-to-market decisions; owning product launches end to end, structuring pilots, and determining how to enter new segments.
• Run win/loss analysis and competitive intelligence programs to inform how we sell and how we position.
• Mentor early career team members including product marketing, content marketing and field marketing.

Senior Product Marketing Manager

Engineering Manager

• Enable our data engineers to become highly productive members of their cross-functional teams, empowering them to ship high-quality, reliable data platforms and pipelines on a daily basis.
• Grow the teams by attracting great talent from your network.
• Foster an inclusive and caring culture where everyone can do their best work.
• Provide regular 1:1 coaching and feedback to tap into the potential of all your team members and help them thrive and reach their aspirations.
• Be a strategic partner to product managers, machine learning engineers, and other stakeholders within your domains and ensure that we are making the correct data architecture and platform decisions that balance short and long term goals.
• Ensure suitability of the data architecture, pipelines, and data models within your domains to enable longer term product, analytics, and machine learning goals.
• Work closely with the other Product & Engineering leaders on strategy, technology and people, including improving our data engineering practices and introducing capabilities that can accelerate data access, reliability, and unlock new product and data-driven opportunities

Staff Product Manager, Machine Learning

Senior Product Marketing Manager

Engineering Manager, Full Stack, Data