Edo is an independent company with strategic investment from McKinstry and Avista.Decarbonizing our electricity system is foundational to reducing our collective greenhouse gas emissions. At Edo, we work every day to create an energy system that is reliable, equitable, and carbon-free.The fundamental infrastructure and regulatory compact of our electrical grid were designed for a different time and is hindering our ability to achieve our environmental and economic goals. We cannot solve this problem at the individual building scale - it's not economically or technologically feasible. Edo will empower utilities and built environment leaders through a partnership model that unlocks rapid innovation towards the grid of the future. We must reimagine a physical and virtual grid that connects nodes of prosumers. We will develop the technology and knowledge platform necessary to achieve impact through scale.The Opportunity with EdoWe are looking for a Building Data Science Engineer to join Edo's R&D team, where you will develop tools to optimize energy use in buildings, reduce carbon emissions, and develop novel control sequences to shift and shed building load to reduce congestion on the electricity grid.You will work closely with Edo's Software Development team and Edo's Operations team to analyze timeseries data from buildings, visualize insights and develop novel machine learning models to forecast and optimize building operations.Ideally, you will have industry experience analyzing timeseries data from equipment systems in buildings, developing analytics and key performance indicators (KPIs), and using machine learning to forecast and optimize building performance. We are primarily looking for candidates with strong backgrounds in three areas: (1) building energy engineering, including HVAC and electrical systems; (2) data science, including core concepts like data cleaning and normalization, linear algebra, statistics, and time series analysis; and (3) programming, particularly contributing to Python data science packages and Jupyter notebooks.Our solutions operate on massive amounts of streaming data, and you will gain experience deploying models in the cloud and on edge devices. You will also work closely with domain experts to build a deep understanding of the electricity grid, commercial building optimization, and opportunities for developing a carbon-free future. Additional responsibilities include:Conduct time series analysis on data streaming from equipment systems in buildings, and extend methods for cleaning, normalizing, and imputing missing data.Collaborate with the software development team to develop and improve machine learning algorithms for time series forecasting, fault detection, optimal control, and classification.Propose novel solutions to problems, design experiments, test hypotheses, and improve predictive models.Evaluate the performance of trained models in production environments, and tune models as necessary.What You Need to Succeed at Edo:Degree in Engineering, Physics, Computer Science, or a closely related quantitative field. Masters level preferred, but not required.Three or more years of industry experience using data from equipment systems in buildings to evaluate performance and identify opportunities for improvement.Three or more years of software development experience, particularly python data science tools and collaboration tools like Jupyter notebooks and GitHub.Three or more years of industry experience using data science and/or machine learning.Familiarity with data analysis and machine learning techniques, including data cleaning, normalization, imputation, feature selection, hyperparameter tuning, error analysis, and ensemble modeling.Excellent communication skills with technical and non-technical audiences.Experience with SQL and/or time series databases