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A Retail Energy Provider (REP) is searching for a data-oriented, quantitative professional to evaluate and enhance existing load forecasting models used in the short- and long-term load forecasting process, and to develop new load forecasting models for their electricity and gas load. The position will examine the accuracy of the existing models by comparing the forecast to actual results, will identify and implement new assumptions and calculations in the model and will test new models to be used by the team in daily operations. Additional data mining will be done for customer profiling and segmentation purposes. This position supports and interacts with multiple teams; stakeholders include load forecasters, portfolio management, supply trading, risk and marketing.
Educational and professional requirements include an advanced degree (Masters degree) in Mathematics, Computer Science, Economics, Engineering, Statistics or other quantitative field; 3-5 years’ experience in a statistical load forecasting role; strong mathematical and statistical modeling skills; Knowledge of regression modeling neural-networks, regression, time series, etc.); Advanced SQL coding skills with exposure to R, Matlab and/or Stata; Understanding of deregulated retail or wholesale power and/or gas markets and customer profiling and segmentation; and Ability to research industry trends and extract and analyze large data sets and use Big Data / Data Science concepts.
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