Senior Quantitative Analyst, Data Science

Key Skills

Data Analytics, Data science techniques, Machine learning techniques, Python Programming, R Programming

Job Description

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 Senior Quantitative Data Scientist of Forecasting. This position will be located in the Hicksville, NY office or Waltham, MA office.

Job Purpose

The Load Forecasting & Analytics team produces electric and gas load forecasts for National Grid. This role will support the delivery of several initiatives within the Load Forecasting & Analytics team that will help modernize National Grid’s electric system in New England creating a network that can accommodate a rising number of distributed energy resources with increased levels of reliability and control. You will develop short term load forecasts and contribute to other projects supporting our forecasting and distributed resource teams. Your key internal stakeholders include Distributed Generation, System Planning, Supply, Engineering and the operational Control Centers. 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, distribution planning and supply procurement.

• Develop short-term forecasts at both the system level and more granular areas such as electric feeders and substations.

• Short-term forecasting using machine learning, regression analysis, neural nets, trees, etc.

• 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, solar, wind).

• 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, 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 planning, supply, engineering, operations) 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, data science or related quantitatively rigorous field.

• 5 or more years of relevant energy industry experience in a regulated setting is preferred.

• Demonstrated experience with econometric or statistical forecasting or modelling required. Knowledge in time series, regression, machine learning, neural networks or similar 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 speak to higher levels of internal leaders, external regulators and other market players. Ability to explain complex technical concepts to non-technical stakeholders.

• Demonstrated experience in modeling with Python and/or R is required. SQL skills preferred. Visualization of results a plus. Knowledge in integrating short-term forecasting processes into company day-to-day operational and IT systems is a plus.

• Advanced Excel skills required.