Senior Data Scientist, Short-Term Forecasting

About us

National Grid is hiring a Senior Data Scientist for Short-Term Load Forecasting. This position will be based out of Waltham-MA, Hicksville-NY or Brooklyn-NY.

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.

The Load Forecasting & Analytics team produces forecasts for customers' electric and gas consumption within National Grid's US service territory. As a Senior Data Scientist for Short-Term Forecasting, you will build short-term (i.e., intra-day to weeks-ahead) electric & gas load forecasts at the system, zonal, and local distribution feeder levels.

The forecasts will be used for supply procurement, operations, engineering, demand-side management, and distributed resources management to improve efficiency, flexibility, safety, and reliability of our systems and assets.

To develop these forecasts, you will apply machine learning and statistical modeling approaches, integrating knowledge of our electric and gas networks and distributed energy resources (including solar and wind generation, demand response, electric vehicle technologies, and battery storage).

Your work will support internal stakeholders including Supply, Engineering, Operations, and others. You will work with the stakeholders to collect their business needs, develop project scope, implement projects accordingly, and deliver the results.

The position of Senior Data Scientist requires the ability to work with others in team-oriented environments as well as work independently, taking initiative and bringing your projects to completion. The ability to speak to both technical and non-technical, internal and external persons to present projects is essential.

• Develop of short-term forecasts for gas consumption, electric power usage, and distributed electric generation at both the system level and more geographically granular levels including towns and neighborhoods.
• Use/build predictive models utilizing multiple linear regression, times series analysis, regression-based machine learning, and/or deep learning, while staying up to date with new developments in these technical areas.
• Support end users with monitoring and analysis of predictions, including forecast performance, interpretation, root-cause analysis, and anomaly detection, to ensure our deliverables meet their needs.
• Ensure the forecasts incorporate distributed energy resources (DERs) like solar, wind, battery storage, demand response, electrification, and other new technologies for a variety of use cases.
• Work with team on process improvement and implement industry best practice.
• Facilitate cross-functionally with data engineers, software developers, and business owners to ensure the broader forecasting pipeline, process, and documentation are efficient, clear, repeatable, and reliable.
• Code collaboratively, contributing to shared code repositories and providing thorough code reviews
• Update forecast processes and documentation to ensure they are efficient, reviewable, and reliable.
• Support other load forecasting teams - long-term electric & gas, data and DERs - on ad-hoc basis and other projects as needed.

• Bachelor's degree (Masters/PhD preferred) in data science, statistics, applied analytics, science, engineering or related quantitatively rigorous field is required.
• Experience using state-of-the-art forecasting models is required. This can include application of time series, regression, machine learning and/or deep learning methods.
• Experience in one or more Python, R and SQL is required.
• Experience in one or more of Databricks, Git and Cloud products is preferred.
• Energy industry experience, especially in the electric or gas sector, is preferred.
• Experience in forecasting customer energy loads is preferred.
• Experience understanding the short-term impacts of weather and distributed resources on loads is useful.
• Experience in forecasting customer energy loads is preferred.
• Experience in visualization tools such as Power BI is useful.
• Strong written and verbal communication skills required, including ability to explain complex technical concepts to non-technical stakeholders.

#LI-Hybrid

#LI-STR1

MA Salary: $130,000 - $153,000 a year

Downstate NY Salary: $139,000 - $164,000 a year

National Grid utilizes an assessment that evaluates the job qualifications/characteristics using AI or statistically based scoring. For more information, please view NYC…