Key skills
PythonAIJupyterAnalyticsGitGitHubCommunicationCollaborationCustomer Success
About this role
Role Overview
- 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.
Requirements
- 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.
Tech Stack
- Python
Benefits
- 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.