UK Longitudinal Linkage Collaboration (UK LLC) is an organisation that provides a trusted research environment (TRE) to systematically link study participants’ data to administrative data. This is an ideal role for someone with an interest in supporting an interdisciplinary research community to complete their projects by managing, curating and understanding new and complex linked data and longitudinal data resources, and disseminating this through working groups and stakeholder liaison.
You will work with a suite of novel and exciting data and have data programming skills which we will support you to improve, and you will have the opportunity to develop specialist skills within our growing team. You will liaise with a wide range of external stakeholders in a fast-paced environment, whilst always working to the highest level of UK Information Governance Standards. There will also be opportunities to write publications, present at conferences, deliver workshops and other externally facing events as this role has a focus on stakeholder liaison.
This is a full-time role, though part-time will be considered at a minimum of 0.8 FTE.
Hybrid working is available: a minimum of 2 days in the office in Bristol, typically Tuesdays and Wednesdays.
UK LLC continues to link new types of data, and the role holder will work within a dynamic and collaborative team, finding creative solutions to enable use of these new data assets.
- Leading the organisation, curation, and supporting provision of new linked administrative data assets.
- Leading the documentation of new linked data to enhance research users' interactions with the data.
- Liaising between data owners' technical teams and the research community.
- Carrying out data processing/descriptive analyses to develop novel understanding, which will be published on GitHub and pre-print publications.
Supporting the research community through working groups to share knowledge and maximise the functionality of these data for research for the public good.
You enjoy working in a fast-paced and dynamic environment with an enthusiastic and diverse team. You are qualified and/ or experienced in working with a variety of complex data types and have exposure to data science tools and coding approaches with a keen interest in developing these skills. You enjoy applying these skills to new scenarios and solving problems whilst developing new methods and are keen to further improve your skills. You are a competent communicator with an interest in liaising with researchers and stakeholders.
Contract type: Open-ended with funding until 31/05/2028
Work pattern: Full-time/ 1 FTE (part-time considered at a minimum of 0.8 FTE)
Grade: J
Salary: £44,746- £50,253 per annum
School/Unit: Bristol Medical School
Shift pattern: 35h/week
This advert will close at 23:59 UK time on 15/09/2026
For informal queries please contact: Katharine Evans (Senior Data Manager (Governance & Users), [email protected]
We recently launched our strategy to 2030 tying together our mission, vision and values.
Available documents
UK Longitudinal Linkage Collaboration (UK LLC) is an organisation that provides a trusted research environment (TRE) to systematically link study participants’ data to administrative data. This is an ideal role for someone with an interest in supporting an interdisciplinary research community to complete their projects by managing, curating and understanding new and complex linked data and longitudinal data resources, and disseminating this through working groups and stakeholder liaison.
You will work with a suite of novel and exciting data and have data programming skills which we will support you to improve, and you will have the opportunity to develop specialist skills within our growing team. You will liaise with a wide range of external stakeholders in a fast-paced environment, whilst always working to the highest level of UK Information Governance Standards. There will also be opportunities to write publications, present at conferences, deliver workshops and other externally facing events as this role has a focus on stakeholder liaison.
This is a full-time role, though part-time will be considered at a minimum of 0.8 FTE.
Hybrid working is available: a minimum of 2 days in the office in Bristol, typically Tuesdays and Wednesdays.
UK LLC continues to link new types of data, and the role holder will work within a dynamic and collaborative team, finding creative solutions to enable use of these new data assets.
- Leading the organisation, curation, and supporting provision of new linked administrative data assets.
- Leading the documentation of new linked data to enhance research users' interactions with the data.
- Liaising between data owners' technical teams and the research community.
- Carrying out data processing/descriptive analyses to develop novel understanding, which will be published on GitHub and pre-print publications.
Supporting the research community through working groups to share knowledge and maximise the functionality of these data for research for the public good.
You enjoy working in a fast-paced and dynamic environment with an enthusiastic and diverse team. You are qualified and/ or experienced in working with a variety of complex data types and have exposure to data science tools and coding approaches with a keen interest in developing these skills. You enjoy applying these skills to new scenarios and solving problems whilst developing new methods and are keen to further improve your skills. You are a competent communicator with an interest in liaising with researchers and stakeholders.
Contract type: Open-ended with funding until 31/05/2028
Work pattern: Full-time/ 1 FTE (part-time considered at a minimum of 0.8 FTE)
Grade: J
Salary: £44,746- £50,253 per annum
School/Unit: Bristol Medical School
Shift pattern: 35h/week
This advert will close at 23:59 UK time on 15/09/2026
For informal queries please contact: Katharine Evans (Senior Data Manager (Governance & Users), [email protected]
We recently launched our strategy to 2030 tying together our mission, vision and values.
Available documents
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