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For Companies At a Glance
- Tasks: Lead projects, analyse data, and mentor junior data scientists in a collaborative environment.
- Company: Join National Grid, a leader in sustainable energy solutions, committed to a greener future.
- Benefits: Enjoy a competitive salary, bonuses, flexible benefits, and a supportive work culture.
- Why this job: Make a real impact on energy sustainability while working with cutting-edge technology and diverse teams.
- Qualifications: Strong Python skills, SQL knowledge, and experience in machine learning and project leadership required.
- Other info: Hybrid working model available; applications encouraged before the closing date.
The predicted salary is between 55000 - 70000 £ per year.
About Us
At National Grid, we light up the world by harnessing the unique strengths of our people. Join us as a Lead Data Scientist to be part of a team that\’s driving forward the energy transition, creating a brighter, more sustainable future for all. Unleash your superpower and bring energy to life.
National Grid is hiring a Lead Data Scientist – This position is based from our Warwick office however we offer flexible hybrid working options.
Job Purpose
Join us as a Lead Data Scientist, where you\’ll be at the forefront of transforming intricate operational and planning challenges within ET and NOI into tangible business success!
In this dynamic role, you\’ll collaborate with ET operational leaders, portfolio managers, planners, engineering teams, and product lines to identify high-impact problems. By leveraging cutting‑edge predictive, optimisation, and automation techniques, you\’ll drive significant improvements in outcomes.
Your ability to turn vague business pain points into structured analytical opportunities will be key. You\’ll craft clear hypotheses, define data requirements, and develop compelling value cases that resonate across the organisation.
As you tackle complex operational and strategic questions, you\’ll create structured analytical frameworks that lead to actionable insights. Your focus on success metrics and value cases will ensure that your work delivers real results.
You\’ll not only develop models that provide actionable outputs but also establish robust feedback loops to continuously monitor model performance and the business impact achieved. Embrace the challenge and make a difference in our organisation!
What You\’ll Do
Strategic Alignment & Opportunity Identification
- Translate ET and NOI strategic priorities into a focused Data Science agenda.
- Identify, assess and prioritise highvalue opportunities where analytics, optimisation, or automation can materially improve performance.
- Engage business leaders, operational teams, planners, and product lines to surface pain points and turn them into structured analytical problems with hypotheses and measurable value.
- Connect with programmes and initiatives across ET to ensure alignment, avoid duplication, and embed Data Science where it delivers the most value.
Data Science Roadmap Ownership
- Develop and maintain a coordinated Data Science roadmap aligned to ET\’s strategic objectives.
- Prioritise opportunities based on business value, feasibility, and strategic impact.
- Ensure transparent sequencing, governance, and communication of roadmap progress, risks, and dependencies.
- Track realised business value and embed feedback loops to monitor model performance and adoption.
Delivery Oversight & Model Lifecycle Management
- Lead delivery of roadmap initiatives from exploration through to PoC, pilot, and production deployment.
- Manage delivery of proofofconcepts and oversee the transition of successful models into operational use.
- Oversee the ongoing support, refinement, and optimisation of existing Data Science assets.
- Set and maintain high standards of analytical rigour, documentation, reproducibility, and model robustness.
Stakeholder Engagement & Communication
- Build strong relationships across ET to understand evolving needs and influence where Data Science can drive value.
- Communicate analytical findings, model outputs, and value in accessible, business‑focused language.
- Educate stakeholders on the capabilities and limitations of Data Science, promoting informed decision making and realistic expectations.
Team Leadership & Capability Building
- Build, lead, and develop a high‑performing Data Science team.
- Hire, coach, and retain talented Data Scientists with a mix of technical and business‑facing skills.
- Provide technical leadership, mentorship, and development pathways for team members.
- Foster a culture of curiosity, innovation, continuous learning, and excellence in analytical practice.
- Maintain awareness of the wider Data Science landscape and bring best practices, tools, and methodologies into ET\’s capability.
About You
- Significant experience using Data Science to deliver tangible benefits for organisations –
- A good understanding of the evolving ML/AI technology landscape and recent advances/best practice –
- Experience hiring, coaching and leading a team –
- Experience operating at all levels of an organisation, with a focus on influencing, capturing opportunities and requirements, and explaining analytics to non‑technical stakeholders
- Experience developing and implementing a data/analytics strategy within an organisation
- Experience of project management frameworks and their implementation (preferably an Agile methodology)
- Experience delivering both proof of concepts and production Data Science models
- Fluency in Python and common Data Science packages, (e.g. pandas, scikit‑learn) tools for lightweight app creation (e.g. streamlit/Flask) and visualisation frameworks (e.g. matplotlib/seaborn/plotly)
- Experience with good software development practices and standard tools (e.g. Git) –
- Experience quality assuring, testing and troubleshooting code and models
- Experience coaching and developing technical skills in others
What You\’ll Get
A competitive salary between £63,000 – £80,000 dependent on capability
As well as your base salary, you will receive a bonus of up to 30% of your salary for stretch performance and a competitive contributory pension scheme where we will double match your contribution to a maximum company contribution of 12%. You will also have access to a number of flexible benefits such as a share incentive plan, salary sacrifice car and technology schemes, support via employee assistance lines and matched charity giving to name a few.
More Information
This role closes at midnight on 2nd Febuary 2026; however, we encourage candidates to submit their application as early as possible and not wait until the published closing date as this can vary.
National Grid Electricity Transmission (NGET) is at the heart of energy in the UK. The electricity we provide gets the nation to work, powers schools and brings energy to life. Our energy network connects the nation, so it\’s essential that it\’s continually evolving, advancing and improving.
In NGET we are passionate about both operating our network safely and providing highly reliable quality of supply for our customers. At the heart of achieving these outcomes is the effective control and operation of our network.
To find out more about us, please follow the link below:
https://www.nationalgrid.com/electricity-transmission/
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At National Grid, we work towards the highest standards in everything we do, including how we support, value and develop our people. Our aim is to encourage and support employees to thrive and be the best they can be. We celebrate the difference people can bring into our organisation, and welcome and encourage applicants with diverse experiences and backgrounds, and offer flexible and tailored support, at home and in the office.
Our goal is to drive, develop and operate our business in a way that results in a more inclusive culture. All employment is decided on the basis of qualifications, the innovation from diverse teams & perspectives and business need. We are committed to building a workforce so we can represent the communities we serve and have a working environment in which each individual feels valued, respected, fairly treated, and able to reach their full potential.
Please note that in most cases, National Grid is unable to offer sponsorship for employment under the UK points‑based immigration system. As such, applicants must have the legal right to work in the UK without requiring sponsorship now or in the future under the UK points‑based immigration system. However, in exceptional circumstances where there is a clear and demonstrable need for specialist skills that cannot be sourced from the local labour market, National Grid may consider offering sponsorship. All applications are welcome from candidates who meet these requirements, regardless of race, nationality, or ethnic origin.
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Lead Data Scientist employer: National Grid
Contact Detail:
National Grid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Familiarise yourself with National Grid's mission and values. Understanding their commitment to sustainability and how data science plays a role in achieving this can help you align your discussions during interviews, showcasing your passion for the energy sector.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that demonstrate your ability to handle large datasets and apply machine learning techniques.
✨Tip Number 3
Prepare to discuss your experience in leading projects. Think of specific examples where you've successfully managed a team or collaborated across departments, as this will be key in demonstrating your leadership capabilities.
✨Tip Number 4
Network with current or former employees of National Grid. Engaging with them can provide insights into the company culture and expectations, which can be invaluable when tailoring your approach during the interview process.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, machine learning, and programming, particularly in Python and SQL. Emphasise any leadership roles or projects you've managed that align with the responsibilities of a Lead Data Scientist.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sustainability and how your skills can contribute to National Grid's mission. Mention specific projects or experiences that demonstrate your ability to lead teams and solve complex problems using data.
Showcase Your Technical Skills: Be explicit about your technical expertise in your application. Include examples of how you've used advanced analytics, machine learning, and statistical methods in previous roles. If you have experience with cloud technologies like Azure, make sure to highlight that as well.
Engage with Stakeholders: Demonstrate your communication skills by providing examples of how you've effectively engaged with stakeholders in past projects. This could include translating technical concepts into business language or collaborating with cross-functional teams to achieve project goals.
How to prepare for a job interview at National Grid
✨Showcase Your Technical Skills
As a Lead Data Scientist, you'll need to demonstrate your proficiency in Python and SQL. Be prepared to discuss specific projects where you've applied these skills, and consider bringing examples of your work or code snippets to showcase your expertise.
✨Engage with Stakeholders
Effective communication is key in this role. Practice explaining complex data science concepts in simple terms, as you'll need to engage with various stakeholders. Think of examples where you've successfully translated technical jargon into business language.
✨Highlight Your Leadership Experience
Since this position involves leading projects and mentoring junior team members, be ready to share your leadership experiences. Discuss how you've guided teams in the past, tackled challenges, and contributed to the professional development of others.
✨Demonstrate Your Problem-Solving Approach
Prepare to discuss how you approach complex problems using data analytics. Share specific examples of how you've identified, extracted, and integrated datasets to derive actionable insights, and be ready to explain your thought process during these projects.