Full time: 35 Hours per week
Fixed Term: November 2025 to 31st October 2027
Location: Usher Institute, Edinburgh Bioquarter
We will also consider requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular (weekly) on-campus working. The Usher Institute expects a minimum of 40% on campus working.
The Centre for Population Health Sciences at the Usher Institute within The University of Edinburgh is looking for Data Analyst in Health Data Science and Innovation.
The Opportunity:
This post offers a rare and exciting opportunity to help shape the future of unscheduled and emergency health care in Scotland by harnessing the power of advanced analytics and real-world health data.
You will work in a fast-paced, agile research environment where data meets decision-making. Working in close partnership with senior health care and community care leaders, you will help develop and implement data-driven approaches that generate actionable insights. These insights will drive rapid cycles of service improvement and directly inform frontline health care. This work is fully aligned with Scotland’s Health and Social Care Data Strategy and will contribute to a more responsive, efficient, and equitable health system.
This programme will go beyond data analysis to enable meaningful system-wide transformation. From enhancing urgent care pathways to strengthening community prevention strategies, your contributions will make a real-world impact through data, helping to build a more adaptive health and care system that can meet rising demand with precision and compassion.
Informal enquiries may be directed to Professor Nazir Lone, Professor of Critical Care and Epidemiology (nazir.lone@ed.ac.uk)
Your skills and attributes for success:
- A good undergraduate degree and higher degree in a relevant subject, or able to demonstrate relevant and equivalent experience
- Experience in using statistical programming for data analysis and machine learning/AI, using python or R
- The ability to extract data and a good understanding of transferring and transforming data, for analysis using different statistical packages.
- Good archiving, data management, and organizational skills
- Ability to work well within a multi-disciplinary team
