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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

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

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.