Data Scientist

Lumen Energy is automating clean energy deployment.
To start, we’re making 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: out of 6 million commercial buildings in the US which are responsible for 16% of all greenhouse gas emissions, most of which could save money with solar, fewer than 4% have solar systems today.
We make clean energy widely accessible by abstracting away the complexity of an underlying marketplace of installers, financiers and confusing electrical jargon. Our challenge is to parse massive datasets, deploy advanced models behind the scenes, pre-package financing, all so that we can deliver simple, delightful, and actionable offers to our customers.
Once the decision has been made to go solar, we support our customers with software tools that help manage the processes of securing financing, evaluating bids and selecting a contractor and finally, managing a live solar deployment.
Who We Are
We are a small team of scientists, engineers, designers and entrepreneurs committed to powering our world with clean energy.  We build on experience at Stripe, Google X, Shopify, and US national labs.  While we're early in our journey, we are live with customers, funded by exceptional investors (soon to be announced), and looking to bring on a core team member who can help us expand our impact.  
We are a remote-first company, but get together regularly in San Francisco and are looking for teammates who work within 3 time zones of Pacific Time.

Some of the problems we’re solving on the team:

• Building models that incorporate computer vision to assess the fit of building roofs and parking lots for solar
• Modelling credit risk and revenue optimization across portfolios of solar assets
• Building dynamic pricing models for wholesale energy markets
• Utilizing GIS and satellite imagery to assess the fit of roofs and parking lots for on-site systems
• Running scenarios to determine the optimal mix of on-site energy technologies
• Helping customers assess the least expensive path to net zero emissions

What you'll be doing

• Collaborate with external expert advisors at universities and US national labs
• Analyze and predict customer building energy usage and cost
• Work inside the engineering org and collaborate cross-functionally teams including sales and customer success teams

Required Experience

• Creating and debugging prediction models by working back from business and product needs
• Quantifying uncertainty and expected error of predictions
• Comfort writing in Python and committing code using git collaboratively
• Building a product through automation that produces analytics to display to the user

Stand-out experience

• Experience making computer vision models
• Comfortable working with geospatial data
• Have owned the productionization and monitoring of your own models

We are proud to be an equal opportunity workplace committed to building a team culture that celebrates diversity and inclusion.