Lead Data Scientist

Castleford
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist / Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist / Deep Learning Practitioner

Lead Data Scientist–Up to £65,000 DOE + Bonus & Benefits– Castleford, West Yorkshire or Shiremoor, Tyne and Wear

The Role

Are you an experienced data expert with strong analytical skills? Do you have what it takes to turn complex datasets into valuable insights that shape business decisions? If so, we have an exciting opportunity for you.

We are looking for a Lead Data Scientist to join our System Forecasting team. In this role, you will analyse network data and customer trends to improve our operations and network planning.

If you’re ready to make a real impact in a fast-changing industry, we’d love to hear from you. Apply now to join our team and help shape the future of energy systems.

Key Responsibilities:

Provide technical oversight, support and strategic direction for the governance and analysis of energy systems monitoring and statistically modelled network demand data, including high frequency time series data.
Guide the implementation of the strategic analytic platform, informing development and deployment of workflow tools and apps (MongoDB / Databricks / Azure).
Provide Subject Matter Expertise for data analytics strategy development and on matters relating to the application of DSO data sets, supporting project teams requiring integration of multiple disparate data sets which need to be brought together to provide useful insights.
Deliver change and inform IT investment decisions so that they meet business needs.
The Company

At Northern Powergrid, we power 3.9 million homes and businesses across the North East, Yorkshire, and northern Lincolnshire. Our Power of 10 approach ensures we work as one team, solving challenges and delivering results for our customers.

The Benefits

Enrolment into our double-matched pension scheme.
Annual bonus of up to 15%.
25 days holiday plus bank holidays.
Excellent opportunities for career growth.
Agile working arrangements.
The Person

Qualified to degree level in a relevant subject, appropriate professional memberships desirable.
Ability to demonstrate advanced data and analytics skills, able to analyse complex datasets with originality and creativity to generate comprehensive insight.
Hands-on experience of high frequency time-series datasets and deploying machine learning models through analytics platforms in a Cloud environment.
Customer-centric approach to data management and analysis, ensuring privacy by design, governance, ethics and best practice drive decision making.
Strong written and spoken communication skills – clear, concise, engaging and persuasive
Self-starter with strong work ethic, capable of motivating themselves and others, able to work independently and contribute to team goals, holding high standards for all work output.
Technically curious, willing to develop new IT skills, share knowledge and help others learn.
Ability to manage workload through excellent planning and organising skills with attention to detail.
Good time management skills with the ability to deliver tasks to deadlines

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.