We are seeking a well-organised Health Data Analyst to join the SchistoTrack Group (https://www.bdi.ox.ac.uk/research/schistotrack). You will be part of a team of approximately 16 individuals at Oxford, including DPhils, postdocs, and administrators. The Oxford team works across statistical, machine learning, and image analysis methods.

The primary focus of this role is to manage the unique, highly dimensional data (spatial-temporal, images, biomedical datasets, etc.) generated from the cohort in Uganda through data wrangling and to support the rest of the Oxford and Uganda teams for data analyses. The individual will liaise with the high performance computing team to manage the private computing cluster that supports SchistoTrack.

This role also includes conducting analyses to help write manuscripts or to help finish manuscripts that have been started and left by past members of the group, so interest in infectious disease research is desirable. As this role is a support role, the individual will not have their own area of research. The individual also will provide information to support grant reports, community engagement, and talks prepared by the PI. The Health Data Analyst will take the lead for onboarding any new group members about the coding procedures in the group, processing code that exists, and other compute-based procedures.

This post provides an exciting opportunity to work with diverse data types, address a disease of poverty, and join a multi-disciplinary team employing quantitative approaches to novel biomedical problems. The position is a great opportunity for someone with a strong quantitative background, who would like to gain experience working with a large research team on challenging data science projects. The post is suitable for someone with excellent programming and analytical skills. The candidate will report directly to the study PI, Professor Goylette Chami.

RESPONSIBILITIES

• Design data management processes, data annotation strategies and detailed plans to support reproducible data analysis (at grade 6, contribute towards this)
• Produce reports on data handling and procedures, including recording changes to the databases and datasets in a well-structured manner
• Develop scripts to interrogate datasets, automate tasks, and perform routine statistical analyses (at grade 6, contribute towards this)
• Perform the data wrangling in close collaboration with senior group members to assess, manipulate, clean, and validate large datasets from a variety of sources
• Communicate effectively using a variety of platforms, to present outputs of the work to the Oxford team, and for presentation for community engagement in Uganda
• Keep the PI informed on progress and developments connected with delivery of a particular task
• Act as a source of information and advice to other members of the group on methodologies or procedures (grade 7 only), and actively participate in ongoing research projects
• Maintain confidentiality regarding research data and ensure information governance principles are adhered to across the project and team

The above list is not exhaustive and the role-holder is required to undertake such duties as may reasonably be requested within the scope of the post. All staff are required to act in a professional, cooperative and flexible manner, in line with the requirements of the post.

SELECTION CRITERIA

Essential

• A strong MSc degree in life sciences, statistics, mathematics, or a computational subject such as computer science, physics, or engineering
• Experience in statistical analysis including running standard regressions (at grade 6, the ability to perform statistical analysis and run standard regressions)
• Experience of using R or Python for data manipulation and statistical analysis (if Python, must also learn R)
• Meticulous approach to data handling and documentation, including experience of source control, particularly Git/GitLab
• Strong (grade 7 only) experience of programming and/or scripting in a Linux environment
• Ability to learn Open Data Kit (electronic survey programming)
• Excellent written and oral communication skills in English
• Ability to prioritise workload and to work under pressure on a variety of tasks concurrently

Desirable

• Understanding and/or experience of the use of biomedical/clinical data
• Experience of working in a multidisciplinary team (e.g. a team involving clinicians, scientists, etc.) and/or in wider collaborative groups