Principal Data Scientist

As a multi-award-winning, cloud-based solution provider, we work with leading global brands to implement energy management techniques and cutting-edge automation software to drive industry-wide cost savings. Our technology reduces environmental impact, ensures compliance, and maximises profitability for high-street brands worldwide.

We are looking for a Data Scientist to work at the intersection of smart building technology, IoT, energy optimisation, and predictive analytics. You will work with rich telemetry from connected assets, energy data, and environmental inputs to deliver intelligent, scalable, and automated insights that drive operational efficiencies and improve system reliability.

• Analytics & Modeling: Perform deep data interrogation, build machine learning models, and design experiments to optimise building performance and asset control strategies.
• Framework Development: Develop, test, and deploy advanced analytics frameworks that uncover actionable insights, translating R&D concepts into production-ready algorithms and reusable components.
• Methodology Selection: Evaluate, select, and apply appropriate data science techniques (e.g., regression, classification, clustering, anomaly detection, time series analysis) based on project requirements.
• Business Alignment: Work closely with internal teams to translate business needs into data‑led solutions, ensuring models and insights align with customer needs and expectations.
• Communication: Present complex technical insights clearly and effectively to both technical and non‑technical stakeholders.
• Research & Innovation: Conduct exploratory research and develop prototypes to test hypotheses or emerging techniques. Stay informed of the latest developments in AI/Machine Learning.
• Operational Excellence: Contribute to internal best practices, processes, and documentation to increase team effectiveness and maintain a culture of curiosity and continuous improvement.
• Analytical Drive: A passion for data interrogation with strong analytical thinking and a drive to uncover actionable insights.
• Technical Proficiency: Proficiency in Python or R, using libraries such as pandas, Num Py, scikit‑learn, Tensor Flow, or equivalent.
• Database
  
  Skills:
  
  Highly skilled in SQL.
• Domain
  
  Experience:
  
  Experience working as a Data Scientist, preferably on client‑facing software solutions, within optimisation or energy‑focused applications.
• Statistical Foundation: Strong foundation in statistical techniques and machine learning, including regression, classification, clustering, time series analysis, and pattern recognition.
• Education: Degree in a quantitative discipline such as Applied Mathematics, Statistics, Computer Science, Engineering, or Physics.
• Experience deploying machine learning models in a cloud environment.
• Experience using version control tools (e.g., Git) and working with cloud‑based data platforms.
• Exposure to Agile methodologies and cross‑functional team collaboration.
• Specific domain experience in energy, IoT, or smart buildings.
• Self‑motivated, comfortable with ambiguity, and proactive in identifying opportunities.