Energy Data Scientist

EnergyHub is working to enable a carbon-free, distributed energy future by seamlessly integrating enormous numbers of energy devices with the electric power grid. Our platform coordinates and collects terabytes of data from what will soon be more than 1,000,000 distributed energy devices, such as thermostats, electric vehicles and home batteries. 

Coordinating and evaluating the performance of all of these devices to forecast and estimate the delivered grid value requires state-of-the-art data science, control systems and machine learning. As such, EnergyHub seeks to hire an Energy Data Scientist to join EnergyHub’s Analytics Engineering team. As an Energy Data Scientist you will work closely with other data scientists and analytics engineers to improve the models used for evaluation of our control algorithms. You will collaborate with the Data Science and Power Systems Intelligence team to understand the algorithms and optimizations used in order to improve our performance evaluation and forecasting abilities. You will also contribute to our data management software systems and will become core to the foundation of a future with carbon-free and distributed energy. 

What you will do:

• You will drive the development of M&V methodologies and data science models for more accurate and transparent evaluation of our advanced grid services from fleets of distributed energy resources.
• You will write production-level code, prototype new data products, and apply machine learning algorithms to energy IoT data
• You will work to translate data from one of the largest distributed energy datasets in the electricity industry into actionable insights for electric utilities and other energy industry stakeholders
• You will collaborate closely with stakeholders inside and outside of EnergyHub including Data Engineering, Client Success, Marketing, Sales, Product, and Market Development teams.
• Other duties as assigned

Who you are:

• You are passionate about enabling a carbon-free, distributed energy future
• You thoroughly enjoy finding valuable insights in large, complex datasets
• You have experience with Python and the scientific stack (pandas, numpy, scipy)
• You have proficiency in SQL and understand good data modeling practices (basic ETL/ELT)
• You have a practical comprehension of basic machine learning algorithms and are familiar with popular software packages such as Sklearn and Tensorflow.
• You can explain results from large-scale data analyses to diverse audiences in a way that is clear, interesting and actionable
• You can have fun while working on really hard problems with really smart people