Data Scientist

We are seeking a Senior Data Scientist to enhance the organisation's intelligence capability, enabling insight-driven decision making through the organisation, analysis, modelling and interpretation of complex data sets. You will design and build data products using innovative Artificial Intelligence and Machine Learning techniques, delivering measurable business impact within a fast-paced, agile environment., * Quickly grasp complex business challenges and identify how data, AI and ML can be leveraged to address them.

• Lead end-to-end delivery of complex data science projects from ideation through to deployment, monitoring and support.
• Develop and deploy advanced machine learning, statistical and AI models using scalable cloud platforms (e.g. Azure Machine Learning, Databricks).
• Ensure models are explainable, ethical and aligned with regulatory and business standards.
• Own the full model lifecycle, including monitoring, retraining and performance optimisation.
• Establish and enforce best practices for model governance, version control and documentation.
• Collaborate with data engineers to design scalable data pipelines and ensure data quality and availability.
• Lead code reviews, knowledge-sharing sessions and contribute to team capability development.
• Manage timelines, risks and dependencies to ensure high-quality delivery.

• BSc minimum in a STEM discipline; MSc or PhD strongly preferred.
• 3-5+ years' professional experience in data science with a proven track record of delivering impactful solutions.
• Strong understanding of CRISP-DM, MLOps, Agile delivery and ITIL or similar frameworks.
• Expert-level proficiency in Python and SQL, with sound software engineering practices (modular design, testing, CI/CD).
• Deep expertise across machine learning techniques (ensemble methods, NLP, time-series forecasting, deep learning) and familiarity with model interpretability and fairness tools.
• Strong experience with Microsoft Azure architecture (Azure ML, Azure Synapse) and containerisation (Docker, Kubernetes).
• Advanced statistical modelling, causal inference and experimental design (e.g. A/B testing).
• Ability to communicate insights effectively through compelling data storytelling, including Power BI.
• Experience with MLflow or similar tools for model tracking and reproducibility.

Desirable Experience:

• Domain knowledge within the water industry.

Person Specification:

• Strong stakeholder engagement and client-facing capability.
• Confident communicator, able to translate complex technical concepts for non-technical audiences.
• Assertive and collaborative, with the ability to lead projects and inspire colleagues.
• Experience mentoring junior team members and supporting capability growth.