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Job Title: Data Steward (Research Scientist Grade 8 Position)
Workstation: Durban, South Africa
Application due date: 29th November 2024
Ref No.: WASH 9/2024
Note: Carefully review the submission requirements. Incomplete applications will not be considered.
Project background
The openwashdata community was established in 2023 with the vision for an active global community that applies FAIR principles to data generated in the greater water, sanitation, and hygiene (WASH) sector. The project is managed by the Global Health Engineering group at ETH Zurich and in its first 1.5 years developed a 10-week “data science for openwashdata’’ training programme and established a clear and efficient data publishing workflow for datasets and code that follows FAIR principles and highest standards for computational reproducibility and version control.
The UKZN WASH R&D Centre at UKZN is a strategic partner for a follow-up project on data stewardship. However, over the years, the WASH R&D Centre has amassed a significant amount of data on WASH related topics, including data from the Sanitation Engineering Field-Testing (EFT) Platform and the broader research community.
The goal of the project is to publish this historical data for wider use of the community. The openwashdata team will provide supervision and training for aspects of data management, including data management plans, data privacy, data ethics, and data publication. The training will cover aspects of file organization, file types, and different pathways for collaboration and task management. The outcome is an increase in WASH related data that is published openly.
The WASH Centre is seeking a data steward for a 1-year position, with potential renewal for a 2nd year, who will work with researchers at the WASH R&D Centre and the openwashdata team on data stewardship. The incumbent will be responsible for identifying current data management practices and developing a draft data management strategy for the WASH R&D Centre, publishing at least 10 datasets of two different types that are available to the UKZN WASH R&D Centre. She/He/They will support data science trainings in varying style with several different focus topics and for a variety of audiences
Minimum requirements
A Master’s degree or equivalent, approved qualification in Computer Science, Data Science, Engineering, Media and Communication, Statistics, Development Studies, or related.
Overall total of two years of experience in the following areas:
- Using data science tools (e.g. Git, GitHub, R, Python, RStudio IDE, VS Code, etc.).
- Developing curriculum, facilitating, coordinating, and conducting training sessions.
Submission requirements
Please send applications to Ms Lungile Ndlela on email ndlelal1@ukzn.ac.za and Mr Lars Schoöbitz on email lschoebitz@ethz.ch
The subject line must clearly indicate the position’s reference number (WASH 9/2024).
A link to an online portfolio of previous work that shows programming code for a data analysis project (if no public portfolio exists, a script with programming code can be submitted with the application package).
An updated CV in your current format.
A cover letter (maximum 500 words) that addresses the following statement: “The data we generate belongs to us as individual researchers and I don’t see the benefits of sharing it openly. I feel concerned that people will use my data in ways that I did not intend to and that they may find flaws in my work.”
The total remuneration package will be in accordance with the University rates of pay and will include benefits.
Enquiries and details regarding the post may be directed to Ms Lungile Ndlela, on email Ndlelal1@ukzn.ac.za.
The closing date for receipt of applications is 29 November 2024.
Please send applications to Ms Lungile Ndlela on email ndlelal1@ukzn.ac.za and Mr Lars Schobitz on email lschoebitz@ethz.ch
The subject line must clearly indicate the position’s reference number.
The University reserves the right not to make an appointment to this advertisement.