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