Data Scientist — Data Engineering & Applied AI

"Energy is one of the defining industries of our time central to the global economy, the climate transition, and the future of technology." Alex Pinna \- Founder and CEO

Company Overview

Nationwide Utilities is on a mission to simplify the world of energy procurement, making it hassle\-free and cost\-effective for businesses across various industries. With 25 years of industry experience, our dedicated team of experts is passionate about helping businesses find the perfect energy solutions that align with their unique needs and financial goals.

Job Description

We sit right at that crossroads, helping some of the UK and Europe’s biggest energy users make smarter, greener, and more commercially sound decisions. With over two decades of industry heritage and the momentum of a high\-growth scale\-up, we’re investing heavily in our next chapter: AI\-powered tools, data\-driven systems, automation, and strategic expansion across European markets.

We’re also training every member of our team to harness AI in their own workflow turning insight into action faster and smarter. If you want to apply data science, engineering and AI to real\-world commercial and operational problems in one of the world’s most important sectors, this could be your opportunity.

About the role

We’re looking for a technically strong and practical Data Scientist Data Engineering \& Applied AI to support the development of our data, automation and applied AI capabilities.

This is not a conventional data analyst role. The focus is on preparing, structuring and improving data so it can be used reliably for reporting, automation, forecasting, machine learning and future AI\-enabled systems. You’ll work across data engineering and applied data science, helping to build reusable datasets, improve data quality, create repeatable workflows, and support practical technical solutions across the business.

This role would suit a graduate or early\-career candidate with strong Python, SQL and data science skills who wants to work on real business problems and grow into a broader data, AI and machine learning role. You do not need to be an energy expert from day one, but you should be curious, technically capable, and motivated to learn how data and AI can be applied in the energy and utilities sector.

Why this role matters

Data is becoming central to how modern businesses operate, make decisions and build intelligent systems.

At Nationwide Utilities, we are developing stronger data foundations to support better analysis, smarter automation, forecasting, internal tools and AI\-enabled workflows.

This role is important because good data makes everything else possible: clearer reporting, better decisions, more useful automation, stronger forecasting and more reliable AI systems.

You’ll help build the practical data foundations that support the next phase of our growth.

What you'll be doing

• Collecting, cleaning, transforming and standardising datasets from approved business and market sources


• Creating reusable datasets for analysis, reporting, automation and machine learning


• Building repeatable data workflows using Python, SQL, APIs and related tools


• Supporting schema design, data validation and documentation


• Working with technical, operational and commercial teams to understand data requirements


• Preparing reliable datasets for forecasting, anomaly detection and applied machine learning


• Supporting internal tools, dashboards and AI\-assisted workflows


• Helping improve data quality, consistency and accessibility across the business


• Communicating technical findings clearly to non\-technical colleagues

• Strong Python skills, especially for data work


• Good SQL knowledge


• Experience cleaning, transforming and analysing datasets


• Understanding of structured data, data quality and validation


• Ability to work with data from different sources and formats


• Strong analytical and problem\-solving skills


• Good attention to detail


• Clear communication skills and ability to explain technical work in plain English


• Interest in data engineering, machine learning and applied AI


• Willingness to learn about energy, utilities and commercial data


• A practical mindset focused on building useful and reliable systems

The following would be useful, but not all are required:

• Pandas, NumPy, SciPy


• Matplotlib, Seaborn or other visualisation tools


• scikit\-learn, XGBoost or PyTorch


• R


• APIs and ETL workflows


• Database design


• Cloud platforms, Linux or Docker


• Time\-series analysis


• Forecasting


• Anomaly detection


• Machine learning pipelines


• LLM or AI workflow experience

This role is well suited to someone with:

• MSc in Data Science, Computer Science, AI, Statistics, Mathematics, Engineering or a related subject


• Undergraduate degree in Mathematics, Computer Science, Engineering, Physics, Statistics or another quantitative field


• Graduate or early\-career experience in data science, data engineering, analytics or machine learning


• Academic or project experience working with real\-world datasets


• Previous energy sector experience is not required, but an interest in energy, utilities, markets, forecasting or commercial data would be helpful.

Pay: £36,500\.00 per year

Application question(s):

• Tell us about a data project where you collected, cleaned, structured or transformed data into something useful. What was the problem, what did you build, and what was the result?


• This role involves building reliable data foundations for analytics, automation, forecasting and AI. What interests you most about that kind of work, and what skills or experience would you bring to it?

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