Lead Data Scientist – Energy Domain

Salary: £65,000 - 105,000 per year

Requirements:

• Strong hands-on experience in Python, machine learning, statistical modelling and advanced time series forecasting within enterprise-scale environments.
• Proven experience delivering production-grade analytical solutions using Azure ML, Git, Databricks, MLOps and modern software engineering practices.
• Strong stakeholder management, leadership and communication skills, with experience mentoring teams and translating complex analytical outputs for both technical and non-technical audiences.
• Excellent understanding of model validation, feature engineering, explainability, data quality and governance, along with an appreciation of responsible AI practices, human-in-the-loop decision making and appropriate AI controls.
• A curious mindset with a willingness to adopt approved AI-enabled workflows and automation to improve quality, productivity and delivery outcomes while maintaining professional judgement and accountability.
• Experience working with geospatial data and spatial analytics.
• Experience with AI, including Generative AI and Agentic AI, applied within enterprise environments.
• Experience with energy system modelling, grid analytics, demand forecasting or energy market data.
• Familiarity with distributed computing, Spark, PySpark or cloud-native data platforms.
• Experience developing models for planning, scenario analysis, operational decision support, model governance or regulatory reporting.

Responsibilities:

• Utilise Python for advanced data analysis, exploration, feature engineering and data processing to uncover insights, trends and patterns, leveraging approved AI tools where appropriate to accelerate analysis and improve efficiency while maintaining rigorous validation and review.
• Develop and implement statistical models, machine learning models and algorithms, with a particular focus on time series modelling and forecasting, supporting robust, scalable and explainable solutions for complex energy challenges.
• Lead model development using Azure ML, Databricks and modern MLOps practices, ensuring effective deployment, monitoring, governance and lifecycle management, with appropriate auditability, human oversight and responsible AI guardrails.
• Collaborate with stakeholders and cross-functional teams to translate business challenges into practical, data-driven solutions while mentoring colleagues, conducting code reviews and promoting engineering excellence and knowledge sharing.
• Stay current with advances in data science, cloud technologies and AI, including Generative AI and Agentic AI where appropriate, identifying opportunities to improve ways of working and deliver greater value for clients.

Technologies:

• Agentic AI
• AI
• Azure
• Cloud
• Databricks
• Git
• Support
• Machine Learning
• MLOps
• Python
• PySpark
• Spark

More:

We are Capco, offering a permanent Lead Data Scientist role in our Data & Analytics practice in London on a hybrid basis. This is a hands-on technical leadership opportunity within the energy sector, where we build the models powering the future of energy system planning. We offer high-impact technology and analytics work across complex Energy and Financial Services environments in a collaborative, flat and entrepreneurial consulting culture that encourages innovation. We provide continuous learning, technical training, certifications and career coaching from day one, and we support technical excellence, collaboration and continuous improvement. Our benefits include a discretionary bonus, competitive pension, health insurance, life insurance, critical illness cover, mental health support, family-friendly leave, backup care, holiday flexibility, annual training, a dedicated Business Coach, online GP access and a range of extra perks. We are committed to an accessible recruitment process and value individuality through our #BeYourselfAtWork culture.

last updated 34 week of 2026