The company is looking to solve the problem of catastrophic wildfires and power outages caused by trees and brush coming into contact with power lines by using AI and advanced satellite imagery to pinpoint and prioritize vegetation risks.
Requirements
- Advanced scientific Python experience, including numpy, scipy, scikit-learn, pandas
- Experience with geospatial or satellite data, and tooling such as gdal, rasterio, shapely, fiona, geopandas, QGIS
- Experience with deep learning algorithms, especially as applied to geospatial data, and tooling such as pytorch, tensorflow
- At least 8 years of commercial experience as a Data Scientist or Machine Learning Engineer
- Experience leading small teams organized around projects or initiatives
- Experience at early-stage startups and remote-first organizations
- An understanding of the challenges of working with geospatial data at scale, as well as possible solutions to those challenges
Responsibilities
- Develop new vegetation intelligence products using standard geospatial Python libraries, as well as machine learning and deep learning tools
- Support existing products through data exploration, model improvements, and bugfixes, especially using QGIS, Dagster, Sentry, and Grafana
- Represent the team by leading projects and initiatives, being responsible for planning, execution, delivery, and ensuring the value of our contributions is clear to other stakeholders throughout the organization
- Build the tooling and processes necessary to measure the value and performance of our contributions, and help to make data-driven decisions about where we can have the greatest impact
Other
- Passionate about climate
- Enjoy working in a remote first, fast-moving environment
- You are based in the US ET time zone
- Flexible working environment with a lot of autonomy
- Other benefits like a remote working budget, an educational budget and time to develop new skills
- To be surrounded by an excellent, vibrant, smart team who have each other's back and believe in a culture of openness, tolerance and respect
- Equity and a competitive salary
