Senior Data Scientist

Key Responsibilities

• Develop data-driven models for failure detection, root-cause analysis, maintenance planning, asset reliability, and operational optimisation

• Identify inefficiencies in technical and operational workflows and propose AI-enabled improvements

• Build predictive models for safety, reliability, and risk management, including uncertainty

quantification

• Apply large language models to automate processes, extract insights from unstructured data, and improve knowledge retrieval and decision consistency

• Design AI tools supporting engineering, operations, service, and commercial teams

• Deliver data products with actionable insights and clear business-aligned recommendations

• Develop short- and medium-term forecasting models for asset performance, demand, and resource planning

• Support scenario analysis and planning optimisation

• Collaborate with engineering, manufacturing, operations, and software teams to deploy scalable, maintainable models and continuously improve performance

Qualifications & Experience

• MSc or PhD preferred in Data Science, Applied Mathematics, Computer Science, Engineering, or Physics

• 5+ years of experience applying ML/AI to real-world systems with proven production delivery

• Strong Python skills and experience in time-series analysis, forecasting, statistical modelling, ML, model validation, and lifecycle management

• Experience with large-scale datasets and distributed systems

Nice to Have:
PyTorch/TensorFlow, optimisation, digital twins or physics-informed ML,

DevOps/APIs/cloud platforms, and exposure to energy markets or operational optimisation

Personal Attributes:
Systems thinker, cross-domain collaborator, able to explain complex models to non-experts, pragmatic, curious, and impact-focused