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Role overview This position is for a mid-level Data Scientist with a focus on the Retail business. The successful candidate will play a key role in designing, developing and improving scalable data science solutions and analytical products. The role requires a strong blend of data science, data architecture, data engineering and ML engineering capability, with a focus on innovation, product development and delivering practical business value. The successful candidate will work closely with stakeholders across the Lightstone Group, as well as with clients outside the group. This will provide broad exposure to a wide range of business challenges, data environments and solution opportunities, while creating strong opportunities to learn new skills and contribute to impactful, data-driven outcomes. The successful candidate will be responsible for contributing to a range of projects and team initiatives, including: Designing and improving data architectures that support advanced analytics, machine learning solutions and scalable product delivery. Building, optimising and maintaining robust data pipelines for the ingestion, transformation and delivery of data across multiple internal and external sources. Developing, deploying and maintaining machine learning models and analytical solutions in collaboration with business and production stakeholders. Investigating and evaluating new data sources, technologies and approaches to unlock new commercial opportunities and strengthen existing products. Driving innovation through prototyping and development of new data-driven solutions, products and features. Translating business problems into technical solutions and partnering with stakeholders to deliver practical, high-impact outcomes for internal and external clients. Supporting and improving existing predictive models, analytical products and decision-support tools. Contributing to best practices in code quality, documentation, solution design and deployment processes. Providing input into technical direction, architecture decisions and continuous improvement within the team. Sharing knowledge through peer coaching, technical discussions, team presentations and broader business updates. Requirements Qualifications / Requirements BSc Honours / MSc in Statistics, Mathematics, Computer Science, Data Science, Engineering or a related field preferred Additional Requirements Relevant postgraduate qualification advantageous Experience Minimum 3 years of relevant experience in data science, analytics engineering, machine learning engineering or a related field Proven experience in designing data solutions, building data pipelines and delivering machine learning or advanced analytics projects in production environments Experience in developing innovative data products, analytical solutions or commercially valuable proof-of-concepts Technical skills Very high proficiency in SQL, Python and Power BI Strong experience in data architecture and data pipeline design Strong experience in machine learning engineering, including model development, deployment and maintenance Strong ability to work with, analyse, interpret and communicate complex data Experience designing scalable data workflows and integrating multiple data sources Solid understanding of statistical concepts and machine learning techniques, with practical application in business environments Experience with data modelling, ETL/ELT processes and performance optimisation Ability to prototype and productionise analytical and machine learning solutions Familiarity with software engineering best practices, version control and testing principles Proficient in Microsoft Office suite, with advanced Excel advantageous Professional approach to report writing, documentation and technical communication Familiarity with Agile concepts and their application in a data science and product development environment Experience wo