Lead Data Scientist

National Grid
Warwick
2 days ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Drug Discovery

Lead Data Scientist - Drug Discovery

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/

#LI-KR1

#LI-HYBRID

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.


#J-18808-Ljbffr

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.