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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Data Engineering & Applied AI - **Company:** Nationwide Utilities - **Location:** London, UK - **Salary:** £36,500.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Cloud Computing, Data Validation, Information Engineering, Extract Transform Load (ETL), Database Design, Linux, Python (Programming Language), Machine Learning, NumPy, Standard Sql, SciPy, SQL Databases, Pytorch, Large Language Models, Pandas, Matplotlib, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Docker - **Published:** June 4, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=6fefbc73f68dc851 ## About the Role Do you have experience in SQL?, Do you have a Master's degree?, 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., * 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 Useful skills and experience 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, * 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. ## Description 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., * 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 ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Vectorize all the things! 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