Research Officer & Data Scientist
| Posting date: | 14 January 2026 |
|---|---|
| Salary: | £39,355 to £45,413 per year |
| Additional salary information: | together with USS pension benefits |
| Hours: | Full time |
| Closing date: | 28 January 2026 |
| Location: | Swansea, Wales |
| Remote working: | On-site only |
| Company: | Swansea University |
| Job type: | Contract |
| Job reference: | SU01374 |
Summary
This is a Fixed Term post until January 2028 working full-time.
The Population Data Science group at Swansea University (https://popdatasci.swan.ac.uk/) supports world-leading research to develop cutting-edge analytical tools and methodologies to address the most pressing health research challenges. Home to Researchers & Data Scientists who focus on a range of projects and programmes that seek to improve services and people's lives through population data science research. This multidisciplinary team works in a fast-moving, agile environment and is committed to demonstrating the value of data science to a range of technical and non-technical audiences.
Utilising the Secure Anonymised Information Linkage (SAIL) Databank’s (www.saildatabank.co.uk) rich anonymised population-scale, individual-level, linked data sources to answer important population-level questions that inform policy and evaluate national programmes and projects. We are looking for a Research Officer & Data Scientist to join our team who will work closely with various stakeholders, organisations, and groups. Our team regularly collaborates as part of many funded research projects and programmes nationally and internationally. Applications are sought from applicants with skills and experience in routine data analysis (preferably in health or social care) and a background in any of the following areas: epidemiology, statistics, operational research, or related informatics, to work in research and data science.
The Research Officer & Data Scientist will be part of the Social Care Linked Data Lab (CARE Lab), a multidisciplinary collaboration aiming to advance the understanding of the population receiving care and support in Wales through linked adult social care data with linked health and administrative data sources, to inform service planning and strategies to reduce inequalities, and to demonstrate the value of linked administrative data for adult social care research.
The Population Data Science group at Swansea University (https://popdatasci.swan.ac.uk/) supports world-leading research to develop cutting-edge analytical tools and methodologies to address the most pressing health research challenges. Home to Researchers & Data Scientists who focus on a range of projects and programmes that seek to improve services and people's lives through population data science research. This multidisciplinary team works in a fast-moving, agile environment and is committed to demonstrating the value of data science to a range of technical and non-technical audiences.
Utilising the Secure Anonymised Information Linkage (SAIL) Databank’s (www.saildatabank.co.uk) rich anonymised population-scale, individual-level, linked data sources to answer important population-level questions that inform policy and evaluate national programmes and projects. We are looking for a Research Officer & Data Scientist to join our team who will work closely with various stakeholders, organisations, and groups. Our team regularly collaborates as part of many funded research projects and programmes nationally and internationally. Applications are sought from applicants with skills and experience in routine data analysis (preferably in health or social care) and a background in any of the following areas: epidemiology, statistics, operational research, or related informatics, to work in research and data science.
The Research Officer & Data Scientist will be part of the Social Care Linked Data Lab (CARE Lab), a multidisciplinary collaboration aiming to advance the understanding of the population receiving care and support in Wales through linked adult social care data with linked health and administrative data sources, to inform service planning and strategies to reduce inequalities, and to demonstrate the value of linked administrative data for adult social care research.