Lead Data Scientist, Short term Forecasting

Key Skills

Python Programming, SQL, Big Data Technology, Machine learning techniques, Data Analytics, R Programming, MLOps tools, SAS, Data Engineering, Statistical modeling, Probabilistic Graphical Models, Forecasting, Predictive Modeling, Prescriptive Analytics, Simulation software

Job Description

Lead Data Scientist, Short term Forecasting

• Location Hicksville, New York; Waltham, Massachusetts
• Organization: Data Analysis and Analytics
• Department: TO Quantitative Analysis Gas

As part of National Grid’s continued commitment to safety, all new hires must be fully vaccinated against COVID-19. Anyone unable to be vaccinated, either because of a sincerely held religious belief or medical reason can request a reasonable accommodation.

About us

Every day we deliver safe and secure energy to homes, communities, and businesses. We are there when people need us the most. We connect people to the energy they need for the lives they live. The pace of change in society and our industry is accelerating and our expertise and track record puts us in an unparalleled position to shape the sustainable future of our industry.

To be successful we must anticipate the needs of our customers, reducing the cost of energy delivery today and pioneering the flexible energy systems of tomorrow. This requires us to deliver on our promises and always look for new opportunities to grow, both ourselves and our business.

National Grid is hiring a Lead Data Scientist of Short term Forecasting. This position can be based out of Waltham, MA or Hicksville, NY office.

Job Purpose

The Load Forecasting & Analytics team produces electric and gas load forecasts for National Grid. As a Lead Data Scientist you will develop short term gas & electric load forecasts and contribute to numerous other 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 position of Lead requires the ability to work independently with minimal guidance and communicate to both internal and external stakeholders to present 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 new technologies and policies (e.g. solar, demand response, storage, electrification of heat, moratoriums, 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 in order to provide a service that is fit for purpose.
• Update forecast processes and documentation to ensure they are efficient, reviewable, and reliable. 
• Provide expert testimony before regulators and defend the forecasts. Respond to data requests from regulatory bodies for rate cases and other proceedings.
• Collaborate with internal stakeholders (including supply, engineering, control centers, strategy) regarding forecast methodology and analysis and ensure our deliverables meet their needs.
• Stay current in all policies, regulatory requirements, market trends, and industry standards regarding customer energy use and technologies and programs impacting that use, such as energy efficiency and demand response. 

Supervisory/Interpersonal- Experience Required

•  Effective communication skills including the ability to make persuasive presentations to small and large audiences.
• Track record of developing working relationships quickly and effectively both internally and externally.
• Experience in communicating both internally and externally to the Company.
• Ability to speak effectively to both technical and non-technical persons.

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 National Grid 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. 

More Information

This position has a career path which provides for advancement opportunities within and across bands as you develop and evolve in the position; gaining experience, expertise and acquiring and applying technical skills. Candidates will be assessed and provided offers against the minimum qualifications of this role and their individual experience.