Data Wrangler/Analyst

University of Oxford; Oxford; On-site; GBP 39,000 - 48,000; Full time

Job summary

A prestigious academic institution in Oxford is seeking a Data Wrangler/Analyst to join a renowned lab. Responsibilities include managing and analyzing genomic data and developing data pipelines. Candidates must have an MSc or equivalent, along with substantial data analysis experience and strong communication skills. This position is a full-time, fixed-term role for 3 years, offering a competitive salary package.

Qualifications

• Substantial experience in data analysis.
• Experience in developing and maintaining data pipelines.
• Excellent written and oral communication skills in English.

Responsibilities

• Process, analyze, and manage genomic and health-related data.
• Develop and maintain complex data pipelines.
• Validate and document results for internal analyses.

Skills

Data analysis

Communication skills

Data management

Education

MSc in a scientific or numerate subject

Job description

Data Wrangler/Analyst – Awadalla Lab

Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford, OX3 7LF

Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and treatment of disease.

We are seeking a Data Wrangler/Analyst to join the Awadalla Lab, an internationally recognized team of scientists with significant experience in tool development, data collection and analyses of multi-omic datasets from international sources. The main responsibilities involve processing, analysing and managing genomic/’-omic’ and health-related data from a wide range of sources, including population cohort data and/or single cell as well imaging data. This includes developing and maintaining complex data pipelines, validating and documenting the results, and performing internal analyses to support operational, discovery and translational research, as well as building and improving existing analytical tools.

To be considered, you must hold a MSc in a scientific or numerate subject, or equivalent experience and have substantial experience in data analysis. You will also have excellent written and oral communication skills in English.

This is a full time, fixed term post (part time considered) for 3 years. The closing date for applications is noon on 15 October 2025.

You will be required to upload a CV and a cover letter as part of your online application. The cover letter should clearly describe how you meet each of the selection criteria listed in the job description.

• Contact Person: HR Recruitment
• Vacancy ID: 181309
• Contact Phone:
• Closing Date & Time: 15-Oct-2025 12:00
• Pay Scale: STANDARD GRADE 7
• Contact Email: [e-mail]
• Salary (£): £39,424-£47,779 per annum (including Oxford University weighting)

We are seeking a Data Wrangler/Analyst to join the Awadalla Lab, an internationally recognized team of scientists with significant experience in tool development, data collection and analyses of multi-omic datasets from international sources. The main responsibilities involve processing, analysing and managing genomic/’-omic’ and health-related data from a wide range of sources, including population cohort data and/or single cell as well imaging data. This includes developing and maintaining complex data pipelines, validating and documenting the results, and performing internal analyses to support operational, discovery and translational research, as well as building and improving existing analytical tools.

Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford, OX3 7LF

Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and treatment of disease.

This is a full time, fixed term post (part time considered) for 3 years.