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.