Jonathan Farland, Sr. Data Scientist at DNV GL

Jonathan Farland

Sr. Data Scientist, DNV GL

Jonathan Farland is a technical consultant for DNV GL Energy in the Policy, Advisory and Research group and serves as the lead data scientist on both quantitative and qualitative energy studies. Mr. Farland’s primary focus is on the development of electricity demand forecasting systems that are capable of predicting demand while accounting for emerging or disruptive technologies such as smart grids, storage, photovoltaic cells, and electric vehicles. Developing these predictive models often requires the collection of large amounts of data and information on electricity usage, as well as climatological and economic conditions. Mr. Farland uses R and Python while leveraging the Spark distributed computing framework to effectively deploy model estimation and statistical learning algorithms.


High Resolution Energy Modeling that Scales with Apache Spark 2.0

As advanced sensor technologies are becoming widely deployed in the energy industry, the availability of higher-frequency data results in both analytical benefits and computational costs. To an energy forecaster or data scientist, some of these… Read more