Data Scientist

University of Cape Town; Cape Town; On-site; ZAR 400 000 - 500 000; Full time

Job summary

A leading South African educational institution seeks a Data Scientist to provide data science support for various research projects focusing on climate, environmental, and socioeconomic data. The role entails supporting senior scientists, developing software tools, and contributing to training initiatives. Candidates should have an NQF 9 qualification and a minimum of three years of experience in data science, with proficiency in R and Python. This position is based in Cape Town and offers an opportunity to work on impactful research.

Qualifications

• A minimum of three years of post-NQF 9 qualification experience in data science.
• Experience in coding in R and Python with at least 3+ years total experience.
• Experience with large spatial and/or temporal datasets.

Responsibilities

• Provide data science support to various research projects.
• Develop new software and tools for research needs.
• Support senior data scientists in advanced data analysis.

Skills

R programming

Python programming

Data analysis

Machine learning

Data management

GitHub

High-performance computing

Geospatial data analysis

Education

NQF 9 (Masters) degree or equivalent postgraduate diploma in a relevant field

Job description

Job title: Data Scientist

Job Location: Western Cape, Cape Town

Deadline: January 16, 2026

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Purpose

• The main purpose of this position is to provide data science support to a range of research staff, projects and other activities within ACDI and its associated research groups and centres, such as ASCEND, the PiNC Lab and Climate Risk Lab, working largely with climate, environmental/ecological, and socioeconomic data.
• The Specialist Data Science responsibilities will include supporting senior data scientists in providing advanced data analysis support to research staff, including application of existing software and codes, development of new software and tools, provision of data science consultations and advice to research students and specialist researchers, and contributing to data science training at ACDI. There are associated responsibilities involving provision of data science inputs to research proposal design, the management of datasets for research purposes and supporting senior data science staff in interfacing with UCT’s e-research capabilities. Initial areas of focus 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 related field.

Minimum experience (type and years)

• At least three years of post-NQF9 qualification experience in data science.
• Data management, data processing, coding for advanced analysis, modelling and/or machine learning (2+ years)
• Coding in both R and Python (3+ years total, 1.5+ years in each)
• Working with large spatial and/or temporal datasets (1.5+ years).
• Working with climate and/or environmental data, as well as (optionally) socio-economic data (1+ years).
• Use of online code collaboration platforms such as GitHub (2+ years)
• Data quality management and use of data quality management tools (2+ 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) (1.5+ years).
• Working in cloud computing and/or high-performance computing environments/contexts (1.5+ 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 providing training in data science to researchers and/or analysts
• Experience in installing and running climate, hydrological and other process-based models.

Skills

• 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 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, geography.

Professional registration or license requirements

• None

Closing date

16 Jan 2026

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