Data Science Specialist

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