Find your next tech and IT Job or contract Data Scientist

Data Scientist (Energy) drives the development and delivery of cutting-edge solutions that strengthen the performance and resilience of electricity networks. Operating at the intersection of engineering, data science, and applied research, the role focuses on identifying operational challenges in the energy sector and transforming emerging technologies into practical, real-world applications. This position works collaboratively with Distribution Network Operators (DNOs), universities, research partners, and internal teams to explore innovation opportunities and co-develop impactful solutions. The engineer contributes technical expertise to data-driven initiatives, shaping models, algorithms, and analytical approaches that support decision-making and innovation outcomes. They play a hands-on role throughout the lifecycle of innovation projects, from early idea generation and feasibility assessment through to prototyping, testing, and deployment. Strong communication and collaboration skills are essential, as the role interfaces with engineering, product, consulting, and business stakeholders to design and refine technical solutions that meet sector needs. The ideal candidate brings deep knowledge of energy systems, experience with AI/ML technologies, and strong programming capabilities. Qualifications & Experience: . Experience within the energy sector, ideally focused on electricity networks or smart grids . Experience applying AI/ML technologies in engineering or operational settings . Strong Python programming skills and familiarity with data analysis, machine learning, or simulation frameworks . Ability to collaborate effectively in multidisciplinary teams and explain complex technical concepts to diverse audiences Key Duties & Responsibilities . Work closely with DNOs to understand operational challenges, explore innovation opportunities, and co-develop solutions that enhance network performance and resilience. . Partner with universities and research institutions to translate emerging technologies and scientific advancements into practical, real-world applications. . Contribute technical expertise to data-driven projects, helping shape models, algorithms, and analytical approaches that drive innovation outcomes. . Communicate effectively with engineering, product, consulting, and business teams to design, refine, and deliver technical solutions. . Support the full lifecycle of innovation projects, from idea generation and feasibility analysis to prototyping, testing, and deployment.

Do you want to lead data science and AI at national scale , influencing how billions of pounds of public services are delivered? In this senior leadership role, you will help transform how operational teams use data science, advanced analytics and AI to make smarter decisions, improve services, and meet future demand. What you’ll be doing As Lead Data Scientist (Data Science & AI) , you will: Set the vision and direction for data science and AI across the organisation Lead high‑impact projects from idea to live delivery Work closely with senior leaders and operational teams to identify where data science and AI can make the biggest difference Build and develop a high‑performing, inclusive team , supporting both technical excellence and career growth Champion the responsible and practical use of AI , including new and emerging technologies

This is a rare opportunity to lead and shape a newly established Data Science and Artificial Intelligence function within HMRC’s Valuation Office. You’ll help position the Valuation Office as a practical test‑bed for operational data science and AI , turning ideas into live solutions that support frontline decision‑making and improve public outcomes. You’ll be joining at a pivotal moment, with the freedom to shape: How data science and AI are embedded into operations How teams across the organisation use insight How responsible and innovative AI is adopted in government What you’ll be doing You’ll work at senior level across the organisation, combining technical leadership with strategic influence. This includes: Setting the strategic direction for data science and AI across operational services Leading end‑to‑end delivery of data science and AI solutions, from concept to live use Working closely with Operations to solve real, complex problems Building strong relationships with senior leaders and stakeholders Developing and supporting a high‑performing, multidisciplinary team Championing a culture of innovation, inclusion and continuous learning

As a Senior Data Engineer, you will design and lead the implementation of data flows that link operational systems, analytics & BI platforms. You will be part of the Data Services team, which handles ingesting, storing, maintaining and exposing a variety of datasets. These datasets are used by analysts and data scientists to generate insights and support decision-making. The team is growing, and your role will involve bringing in new datasets, maintaining existing ones, and ensuring data is clean, accessible and high-quality

Looking to apply your data engineering skills to work that directly informs decision-making across the UK? This opportunity sits within the Office for National Statistics, working on large-scale data platforms that support national priorities, from crisis response to economic insight. Why this role stands out Work on AI-augmented data products and pipelines Contribute to national statistics and cross-government data platforms Play a role in high-impact work such as COVID data insights and cost-of-living analysis Collaborate with analysts and data scientists to unlock the value of complex datasets Be part of a team building reusable, automated data engineering solutions What you’ll be doing Designing and building scalable data pipelines Preparing and linking complex datasets for analysis Improving data quality through cleansing, validation and enhancement Translating business needs into technical solutions Supporting and mentoring others in a collaborative team environment

This Lead Data Engineer role sits within DVLA’s data platform team, working on modern, large-scale data systems that drive better decisions, insights and digital services. Why this role stands out Lead engineering for high-impact data products across DVLA Work with modern technologies including Databricks, Spark, and lakehouse architectures Shape standards and best practice across a growing data function Collaborate with product teams, analysts and data scientists Play a key role in improving digital services at national scale What you’ll be doing Leading the design and build of data pipelines and data products Developing robust data models and integrations across systems Ensuring data is processed efficiently for analytics and business intelligence Driving best practice and standards across data engineering teams Supporting performance optimisation and balancing cost, scalability and reliability Working across teams to enable reuse of data and improve delivery

At MI6 (the Secret Intelligence Service), we’re investing heavily in artificial intelligence and machine learning to strengthen how we operate today and prepare for the challenges of tomorrow. As a Machine Learning Engineer , you’ll be a key part of that transformation. You’ll be working at the point where machine learning moves into live, operational use , designing, deploying and maintaining robust capabilities in environments where quality, resilience and trust are paramount. What you’ll be working on In this hands‑on and highly influential role, you will: Design, build and operate mission‑critical machine learning systems Own the end‑to‑end ML lifecycle , from training and fine‑tuning through to deployment and live monitoring Act as the bridge between research and production , ensuring models are reliable, scalable and fit for purpose Shape and improve MLOps practices , infrastructure and workflows Champion explainable, ethical and transparent AI as core engineering principles Collaborate with data scientists, researchers, software engineers and hosting specialists Support and mentor other engineers, helping to raise ML capability across teams