Data Science Specialist

Data Scientist – Bayesian Hierarchical Modelling (R / Python / AWS) Overview We are seeking a highly capable Data Scientist with strong experience in Bayesian hierarchical modelling and advanced statistical techniques to join a growing data and analytics capability. This role sits across data science, data engineering, and backend development, supporting the delivery of scalable models, robust data pipelines, and high-quality insight products. You will work with complex, high-volume datasets, applying statistical rigour to solve real business problems, while also contributing to the engineering layer that enables analytics at scale. Key Responsibilities • Design, build, and deploy Bayesian hierarchical models to support forecasting, inference, and decision-making • Develop and maintain data pipelines and ETL processes, ensuring reliable, clean, and well-structured datasets • Contribute to data “plumbing” and backend data services that support analytics and modelling workflows • Work with large and complex datasets using Python and R • Build and deploy scalable data solutions within AWS environments (e.g. S3, Glue, Lambda, Redshift, or equivalent services) • Develop dashboards and data visualisations to translate complex model outputs into clear, actionable insights for stakeholders • Support backend development where required, particularly around data APIs, pipelines, and integration layers • Collaborate with data engineers, analysts, and business stakeholders to define requirements and deliver end-to-end solutions • Ensure model performance, validation, monitoring, and continuous improvement • Contribute to best practices across data science, engineering, and cloud-based data architecture Key Skills & Experience Essential • Strong experience in Bayesian statistical modelling and hierarchical modelling techniques • Proficiency in Python and R for data science and modelling • Strong grounding in statistical modelling, probability, and inference methods • Experience building and maintaining ETL pipelines and data workflows • Experience with data engineering / data “plumbing” in cloud or distributed environments • Working knowledge of AWS services (e.g. S3, Glue, Lambda, Redshift, or similar) • Experience building dashboards using tools such as Power BI, Tableau, or similar • Strong ability to manipulate, clean, and structure large datasets • Ability to communicate complex analytical outputs in a clear and usable way Desirable • Exposure to backend development (APIs, services, or data layer engineering) • Experience with probabilistic programming tools such as Stan or PyMC • Experience operationalising data science models in production environments • Familiarity with modern data stack tooling and cloud-native architectures • Experience working in Agile delivery teams • Exposure to real-time or large-scale data systems Soft Skills • Strong analytical and problem-solving capability • Comfortable working across both engineering and analytical domains • Strong stakeholder communication skills • Ability to work independently and take ownership of delivery • Commercial awareness and ability to translate data into business value What This Role Offers • Opportunity to work across full-stack data science and data engineering • Exposure to advanced Bayesian modelling in a production environment • Hands-on work with cloud infrastructure (AWS) and modern data pipelines • Opportunity to shape how data is engineered, modelled, and consumed across the business • High-impact role where statistical insight directly influences decision-making