Data Scientist

• Partner with NHS, life sciences, and other healthcare clients to translate complex and ambiguous questions into well-defined analytical problem statements
• Lead the end-to-end delivery of data science workstreams, from scoping and design through to analysis, insight generation, and client presentation
• Act as a trusted analytical advisor within projects, shaping both the analytical approach and the resulting solution
• Apply structured problem-solving approaches to complex healthcare, commercial, and policy challenges
• Communicate insights clearly to non-technical audiences, explaining methods, assumptions, limitations, and implications
• Design and develop predictive models to forecast health outcomes, healthcare utilisation, and medicine sales performance
• Conduct population health analyses, disease burden studies, and real-world evidence (RWE) research using large-scale healthcare datasets
• Apply robust statistical methods to ensure analytical rigour, transparency, and interpretability
• Extract insight from both structured and unstructured data sources, including clinical text and public data
• Ensure analytical outputs are decision-focused and aligned to client objectives
• Design, build, and maintain complex data pipelines integrating multiple disparate data sources
• Ensure data quality, reliability, security, and scalability across analytical solutions
• Apply software engineering best practices to data workflows to support reuse, testing, and long-term maintainability
• Work effectively with cloud-based storage and compute environments
• Write clean, well-structured, reproducible Python code with clear documentation
• Implement unit tests, data validation checks, and quality controls
• Contribute to CI/CD pipelines for analytics and data workflows
• Use Git effectively, including collaborative development, version control, and code reviews
• Manage Python environments using tools such as conda, uv, poetry, pip, or equivalent
• Use Bash and cloud tooling (e.g. AWS CLI) for automation and orchestration
• Build solutions that are production-minded, not purely exploratory
• Lead technical discussions, workshops, and presentations with client stakeholders
• Proactively identify risks, dependencies, and delivery constraints within data workstreams
• Maintain high standards of documentation, reproducibility, and delivery excellence
• Support integrated working between data science and consulting teams

CF

Senior Data Scientist