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