Forecast Model Analyst (Hybrid), California

Job Description

Under the general direction of the Director, participates in developing programs to track, evaluate, implement, and promote forecasting model evolution including production modeling on Short Term Forecasting using Big Data, Machine Learning, Numerical Weather Prediction Models, Artificial Intelligence, and Neural Networks.  Develops and enhances energy efficiency models, demand response models, and other energy models and incorporates their impacts to the Short Term Load Forecast.

What You Will Be Doing:

Participates in the research, development, and implemention of new forecasting tools and interfaces through the use of computer programming. Responsible for validating, integrating, and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results. Enhances current or develops new tools using computer programming languages such as VBA, Python, Perl, etc. Evaluates potential inefficiencies in current procedures and seeks improvements.

Researches, develops, and enhances complex energy efficiency models, demand response models, short term load forecast, wind forecast, solar forecast, uncertainty forecast, and other energy models (i.e., plug in electric vehicles, distributive generation models) through the use of statistical, algorithmic, mining and visualization techniques.

Coordinates and participates in Short Term Forecasting projects to implement new or enhanced features to production enviornments and/or applications.

Conducts post-analysis to evaluate forecast accuracy. Seeks to improve pre-established forecasting goals. Stays abreast of forecasting developments within the demand modeling and meteorological field,  and the impact of such developments to the organization.