Senior Data Scientist at University of Cape Town

PURPOSE

• The main purpose of this position is to provide data science leadership and support/advice to a range of research staff, projects and other activities within ACDI and its research groups and centres, such as ASCEND, the PiNC lab and Climate Risk lab, working largely with climate, environmental/ecological, and socioeconomic data.
• Data science leadership responsibilities will include coordination and management of data science activities at ACDI, coordination of data science training, mentoring of junior data scientists, data infrastructure design, development, and governance, being the main point of contact with UCT’s e-research capabilities.
• Data science technical and support responsibilities will include advanced data analysis, application of existing software and codes, development of new software and tools, including machine learning, and provision of data science consultations, support and advice to specialist researchers and research teams. The position will also require leading the data science inputs for grant proposals developed within ACDI. Initial areas of focus of the position will be data science at the intersection of climate science and climate impacts modelling (health, hydrology, ecology).

Minimum qualifications
NQF 9 (Masters) degree or equivalent postgraduate diploma qualification in an appropriate field: data
science, information systems, computer science, climate science, quantitative ecology/environmental
science, statistics, bioinformatics or a closely related field.

Minimum experience
(type and years)
Required

• At least five years of post-NQF9 qualification experience in data science.
• Data management, data processing, coding for advanced analysis, modelling and/or machine learning
• (3+ years)
• Coding in both R and Python (5+ years total, 2+ years in each)
• Working with large spatial and/or temporal datasets (3+ years)
• Working with climate and/or environmental data, as well as (optionally) socio-economic data (3+
• years).
• Use of online code collaboration platforms such as GitHub (4+ years) and management of collaborative
• projects on these platforms (2+ years)
• Data quality management and use of data quality management tools (3+years).
• Provision of advanced data science service to support the research enterprise (such as developing and
• improving data processing and analysis workflows, working with specialist scientists to identify and
• implement data science analyses for specific research questions) (3+ years).
• Working in cloud computing and/or high-performance computing environments/contexts (3+ years)
• Teaching or training of data science and/or other quantitative skills (1+ years)

Advantageous

• Tertiary level training (e.g. BSc) and/or several years work experience in one or more relevant subjects,
• such as climate or atmospheric science, oceanography, ecology, hydrology, health sciences,
• environmental economics, conservation science.
• Experience in installing and running climate, hydrological and other process-based models.
• Leading or support on institutional research data governance and management

Skills

• Capability to manage or coordinate a data science team and lead on data science governance and
• management in a research setting.
• Ability to provide inputs on data science into institutional strategic planning and research proposals
• Teaching/training students and/or researchers in data science
• Excellent data science skills including programming in languages and software environments for
• advanced analysis, modelling and/or machine learning.
• Highly proficient in both R and Python to support diverse analysis needs of researchers at ACDI; skills
• in SQL would be an advantage.
• Ability to provide advanced data science service to support the research enterprise (such as developing
• and improving data processing and analysis workflows and/or working with specialist scientists to
• identify and implement data science analyses for specific research questions).
• Proficient in the management and use of online collaborative code platforms such as GitHub, and ability
• to train/support researchers in using such a platform.
• Able to maintain and install data science software in multiple operating system environments
• (Linux/Unix, MacOS, Windows). Ability to install and maintain process-based models on Linux/Unix
• would be an advantage.
• Proficiency in working in a high-performance computing (HPC) environment. Capability to procure,
• mission and maintain small HPC machines would be advantageous.
• Proficient in sourcing, processing and analysing large geospatial datasets such as climate model data,
• land-surface datasets, and/or earth-observation datasets.
• Proficient in data quality management and use of data quality management tools in a research
• environment.
• Works well in a team, and able to understand key scientific concepts in the natural sciences.
• Strong written and verbal communication
• High numeracy, demonstrating high levels of attention to detail
• Enjoys working with and validating data (including spatial and temporal data)
• Excellent written and verbal communication skills.
• Ability to work effectively in interdisciplinary teams.
• Meticulous attention to detail

Knowledge

• Expert technical specialist knowledge of data science, statistics, and/or bioinformatics
• Good knowledge (e.g. through experience or tertiary level courses) in one or more fields relevant to
• ACDI, such as climate science, hydrology, ecology, public health, economics, 

Closing date

16 Jan 2026