Data Science Manager: Lead AI & Analytics for Energy

National Grid; Greater London; Hybrid; GBP 78,000 - 91,000; Full time

Benefits offered by this job

Competitive pension scheme

Annual bonus up to 30%

Flexible benefits (cycle scheme, share

Digital GP service

Access to Work + Family Space

Job summary

National Grid is seeking a Data Science Manager to lead a high-performing Data Science team across the organisation. You will stay hands-on, building AI models, coding, and turning data into clear, actionable insights in a fast-paced, agile environment.

You will collaborate across the UK and US with Gas, Electric, and support functions, delivering impactful data products while shaping the future of energy through data-driven decisions.

Qualifications

• Demonstrated Data Science experience, preferably in energy/utility sector.
• Proven ability to lead, mentor, and develop Data Scientists to deliver high-quality work.
• Strong communication and stakeholder engagement, translating data into business insights.

Responsibilities

• Lead and inspire a team of Data Scientists across the organisation.
• Develop advanced analytics and AI solutions using ML, statistical modelling and forecasting.
• Integrate data from multiple sources to build robust datasets for insights.
• Deliver cross-UK/US projects in collaboration with Gas, Electric and support functions.
• Continuously explore new ideas and technologies to advance energy data solutions.

Skills

Data Science

Team leadership

Stakeholder engagement

Python

SQL

GenAI

Data visualization

Cloud (Azure)

GIS (ArcGIS)

Tools

Python

SQL

Azure

Power BI

ArcGIS

Job description

National Grid is seeking a Data Science Manager to lead a high-performing Data Science team across the organisation. You will stay hands-on, building AI models, coding, and turning data into clear, actionable insights in a fast-paced, agile environment.

You will collaborate across the UK and US with Gas, Electric, and support functions, delivering impactful data products while shaping the future of energy through data-driven decisions.