Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Head of Data Science

National Grid
Canterbury
1 week ago
Create job alert

The Opportunity

Every day, we deliver safe and secure energy to homes, communities, and businesses, connecting people to the energy they need for their lives. Our expertise and track record position us uniquely to shape the sustainable future of our industry as the pace of change accelerates. To succeed, we must anticipate customer needs, reduce energy delivery costs, and pioneer flexible energy systems. This requires delivering on our promises and seeking opportunities for growth.

In IT & Digital, we collaborate closely with the diverse energy businesses within the National Grid group, revolutionizing operations through technology. Embracing modern methodologies and Digital mindsets, we drive efficiency and bring new capabilities to internal and external customers as we lead the charge toward a carbon-free future.

Our work is critical, as National Grid powers millions of homes and businesses in the UK and US, and the technology we employ is vital to this task. The successful applicant for this position will play a crucial role in our mission, supported by our multicultural, customer-centric global team, with opportunities for professional development.

As the Head of Data Science, you will be a key leader within the Chief Data Office, driving the development and implementation of Data Science and AI initiatives that deliver quantifiable business value. You will oversee our Data Science teams, ensuring that our data science and AI projects inform critical business decisions across all of our Business Units.

Your expertise will help optimize National Grid’s operations, improve safety & reliability, and improve customer experiences by leveraging advanced analytics, data science, and AI/GenAI techniques.

#LI-XXX #LI-Hybrid

What You'll Do

Lead and manage the flexible Data Science delivery teams (pods), ensuring alignment with business objectives and fostering a culture of innovation, collaboration, and continuous learning.
Strategy delivery: Execute the AI Strategy, setting clear goals and priorities in line with business needs and company vision.
End-to-end development: Own the end-to-end development of AI initiatives, from concept to validation of the AI solution with the business, ensuring the delivery of actionable insights that drive business impact.

AI Solution Deployment: Work with Head of ML Engineering to ensure that AI solution deployments are on track and are consistent with business expectations
Cross-functional collaboration: With senior leadership, platform, engineering, and operations teams to understand needs and translate into action plans.
Model Development: Oversee the creation of predictive models, machine learning algorithms, and data-driven insights that solve complex business challenges.
Thought Leadership: Stay ahead of industry trends in data science and AI (including Generative AI) to implement cutting-edge technologies and techniques.

About You

Education:

  • 10+ years of experience in data science or equivalent, with at least 5 years in a leadership or management role.
  • Advanced degree (Master’s or Ph.D.) in a quantitative field such as Data Science, Computer Science, Statistics, or Mathematics is preferred.


Leadership: Demonstrated experience in overseeing multiple teams comprising technical specialists (including data scientists, machine learning engineers, data engineers) as well as functional specialists (e.g. product owners)
Communication & Stakeholder Management: Demonstrated ability to influence and collaborate with cross-functional teams and senior stakeholders, including technical and non-technical colleagues.
Utility expertise: Strong track record in the regulated utility space, ideally at an IOU.
• Functional expertise in data science, statistical modelling, data analysis, and AI techniques.
Programming: Proficiency in Python and SQL.
Data Insights: Deep knowledge of data manipulation, data visualization, and data wrangling with experience in tools like, Power BI.
Cloud Platform: Hands-on experience - preferably with Azure (AWS and GCP also considered).
Business Process: Strong understanding of business processes within at least one of the following domains: gas and electric operations, finance, customer experience, HR, legal and compliance, with the ability to translate business problems into data-driven solutions.

Your Rewards

Rewarding work and a collaborative, team-oriented culture are just the beginning. Review our digital benefit guide at ngbenefitslivebrighter.com for full details and descriptions.

Salary

$198K - $233K a year

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. Internal candidates will be assessed and provided offers against the minimum qualifications of this role and their individual experience.

National Grid is an equal opportunity employer that values a broad diversity of talent, knowledge, experience and expertise. We foster a culture of inclusion that drives employee engagement to deliver superior performance to the communities we serve. National Grid is proud to be an affirmative action employer. We encourage minorities, women, individuals with disabilities and protected veterans to join the National Grid team.

National Grid utilizes an assessment that evaluates the job qualifications/characteristics using AI or statistically based scoring. For more information, please view NYC Local Law 144 .
#J-18808-Ljbffr

Related Jobs

View all jobs

Head of Data Science

Head of Data Science

Head of Data Science

Head of Data Science

Head of Data Science

Head Of Data Science

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.