Our customer is automating clean energy deployment. They make getting a fully-financed clean energy system for a commercial building as easy as applying for a credit card. The scope of the opportunity is massive: fewer than 4% out of 6 million commercial buildings in the US currently use solar.
You will work with a small team of scientists, engineers, designers, and entrepreneurs committed to powering our world with clean energy.
- Help to build the engine that allows for automatic evaluation of the economic potential of a building for on-site energy
- Collaborate with data scientists internally and in national laboratories to implement data models to predict energy use, utility costs, building characteristics, and potential savings
- Integrate with an emerging suite of software tools and APIs to further modeling capabilities
- Build out a multi-sided user-facing platform for building owners, tenants, installers, and financiers to orchestrate a complicated process with intuitive software
- You have experience building full-stack web applications and are comfortable building in Python
- You're ready to take on a high level of responsibility as part of a small team that moves quickly
- While you understand how to build systems that scale you also understand the tradeoff between technical debt and speed, and are comfortable making informed decisions
- Nice to haves: Experience managing data pipelines and deploying ML models, comfort with Docker and managing CI pipelines, familiar with GIS