across data, AI, software engineering, product, QA and delivery to create practical outcomes for clients and end users. Key responsibilities Lead the design, development, validation and deployment support of data science models and analytical products. Apply advanced techniques such as machine learning, NLP, forecasting, optimisation or simulation where appropriate. Guide … colleagues on data preparation, feature engineering, model selection, validation and interpretation. Work with data engineers and software teams to make data science outputs scalable, maintainable and usable. Communicate complex findings, uncertainty and limitations clearly to stakeholders and delivery teams. Promote responsible AI, data ethics, privacy and model governance within projects. ...
