Solutions Engineer

🕒 vor 22 Tagen

🗣️🇺🇸🇬🇧 Englisch erforderlich

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Overstory

11 - 50 Mitarbeiter

🤖 Künstliche Intelligenz

⚡ Energie

☁️ SaaS

Artificial Intelligence • Energy • SaaS

Overstory ist ein Unternehmen, das umsetzbare Vegetationsinformationen für Versorgungsunternehmen bereitstellt, um ein sichereres und zuverlässigeres Energiemanagement zu ermöglichen. Ihre Software hilft Versorgungsunternehmen dabei, Ressourcen zu optimieren, Vegetationsrisiken zu mindern und ihre Betriebsprogramme zukunftssicher zu gestalten, indem sie datengesteuerte, intelligentere Infrastrukturmanagement ermöglicht. Overstory nutzt fortschrittliche Technologie und Analytik, um beim Vegetationsmanagement zu unterstützen, ein wesentlicher Faktor bei Stromausfällen und Waldbränden. Sie arbeiten mit Versorgungsunternehmen zusammen, um Lösungen zu entwickeln, die sich nahtlos in bestehende Arbeitsabläufe integrieren lassen.

Beschreibung

• On a typical day, you might be: running satellite imagery through a pipeline and validating the output; debugging a geospatial join in Python; reviewing a draft analysis with a Customer Success Manager before it goes to a customer; talking with a utility vegetation manager to walk through findings and adjust based on what you hear; refactoring a notebook into a reusable script for the team; or sketching out how a recurring customer ask could become a product feature. • Ensure our customers get the most possible value out of Overstory through technical and analytical work • Own customer projects end-to-end, from data requests and processing through analysis to customer-ready outputs, in close partnership with Customer Success. • Work with large geospatial datasets (vector and raster) from Overstory's platform, customers, and third-party sources — process, validate, analyze, and turn them into outputs customers can act on. • Build rapport with customer counterparts. Translate technical findings into recommendations that change decisions and lead to better outcomes for our customers. • Build the technical foundations for what we productize next • Identify patterns across customer work that are worth standardizing and productizing. Convert one-off projects into repeatable artifacts. • Strengthen engineering quality so analytical work is easier to validate, hand off, and scale. • Partner with product and engineering to build the productization roadmap. • Strengthen the analytics workflows and infrastructure that support both customer impact and future productization.

🎯 Anforderungen

• 2–4 years of professional experience working with large, complex geospatial datasets in a customer- or stakeholder-facing capacity. • Proficiency with a Python-driven analytical and engineering stack — Python, Jupyter, git/GitHub, and command-line workflows. • Experience successfully managing multiple projects simultaneously. • Demonstrated attention to detail and care with data. • Demonstrable experience (or at a minimum a serious interest in) leveraging AI tooling to amplify your work. • Proven ability to solve ambiguous problems and collaborate effectively with stakeholders. • Excellent communication, including translating technical findings for non-technical audiences and building rapport with customer counterparts. • Passionate about tackling climate challenges with data-driven solutions.

🏖️ Vorteile

• We gather once a year in-person for our unforgettable team gathering event. • We also offer the option to occasionally meet up for in-person collaboration.

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