Mathematical Statistician

Mathematical Statistician

This position is located in Portland, OR which boasts huge spans of amazing trees, foliage, landscape, and everywhere you look you can appreciate beautiful greenery! It is known as the most bike-friendly city in America, has a train system that greets you at the airport spanning across the city, and is home to the Portland International Rose Garden, the oldest in the country! Portland is the one place where you will find lively festivals, energetic music, mouthwatering food, and for you basketball fans, the Portland Trail Blazers are a 7 minute walk from the HQs building! There is always something new to experience in this eco-friendly town!

As a Mathematical Statistician, you will:

• Perform the scientific work of designing, developing, creating or adapting mathematical methods and techniques in statistical processes to carry out short-term (sub-hourly, hourly, out 2 weeks) load analysis. Incumbent is responsible for developing, coordinating, and implementing all studies, analyses, and forecasts.
• Develop load forecasting methods and models for Short-Term (sub-hourly, hourly, out 2 weeks) for operating level loads through the application of complex mathematical/statistical methods.
• Perform continuing mathematical and statistical investigations to evaluate and compare alternative forecasting models relative to actual observed electricity demands.
• Provide timely and high quality subject matter expertise on load changes and supports business operations, marketing meetings, and demand side management meetings.
• Formulate, plan, and execute broad or in-depth economic studies based on analysis of loads associated with a subset of requirements customers (including customers with dispatchable generation), and represent those customers with the most complex issues.
• Compare forecasts with actual obligations, determine the reasons for differences, and assess the impact of those differences on the reliability of future forecasts, market rates, and systems operations.
• Evaluate research, interpret economic and environmental conditions, and test and adjust mathematical models to ensure a close correlation with reality and to ensure that operational changes are based on reliable data.