Senior Quantitative Data Scientist of Forecasting. This position will be in the Hicksville, NY office or Waltham, MA office.Rate: 145KJob PurposeThe Load Forecasting & Analytics team produces electric and gas load forecasts for Clients. You will develop short-term gas & electric load forecasts and contribute numerous gas & electric load forecasting projects supporting our electric, gas, and distributed resource teams. You will support internal stakeholders including Supply, Engineering, Control Centers, Strategy, and others. You will ensure that the forecasts incorporate new distributed energy resources, technologies, and policies.Key Accountabilities
- Develop and implement short-term load forecast models and processes. Perform analysis relating to the forecast, as necessary. Enable processes to be integrated with daily control center operations and supply procurement.
- Develop short-term forecasts at both the system level and more granular areas including electric feeders and gas regulator stations.
- Short-term forecasting using machine learning, regression analysis and neural nets.
- The ability to work and defend results. The ability to speak to both technical and non-technical persons to present projects is essential.
- Ensure the forecasts properly account for distributed energy resources (DERs) and policies (e.g., demand response, electrification of heat, etc.).
- Support other load forecasting teams - long-term electric & gas, data and DERs - on ad hoc and other projects as needed.
- Implement process improvement and best practices; and remain abreast of changing technologies and industry best practices to provide a service that is fit for purpose.
- Update forecast processes and documentation to ensure they are efficient, and reviewable.
- Provide expert testimony before regulators and defend the forecasts. Respond to data requests from regulatory bodies for rate cases and other proceedings.
- Work with internal stakeholders (including supply, engineering, strategy) regarding forecast methodology and analysis and ensure our deliverables meet their needs.
Qualifications
- A Bachelor's degree (Master's preferred) in statistics, applied analytics, engineering or related quantitatively rigorous field.
- 5 or more years of relevant energy industry experience in a regulated setting with direct interaction with regulators is preferred.
- Demonstrated experience with econometric or statistical forecasting or modelling required. Knowledge in time series, regression, machine learning, or neural networks used for forecasting is required. Experience in energy load forecasting preferred.
- Good understanding of industry operations and the regulatory environment is preferred. Knowledge specific to Client is a plus.
- Experience forecasting short and/or long-term impacts of weather and distributed resources on loads is preferred.
- Strong written and verbal communication skills including the ability to testify before regulators and respond to regulatory data requests. Ability to explain complex technical concepts to non-technical stakeholders.
- Python experience is required. Expertise in statistical programming software such as R or SAS preferred. Advanced SQL skills preferred. Knowledge in integrating short-term forecasting processes into company day-to-day operational and IT systems is a plus.
- Advanced Excel skills required.