368 Data Scientists jobs in South Africa

• Conduct advanced research in water chemistry with a focus on agricultural and environmental applications.
• Develop and validate analytical methods for water quality assessment.
• Lead and contribute to national and international research projects.
• Publish research findings in peer-reviewed journals and present at scientific conferences.
• Supervise postgraduate students and mentor junior researchers.
• Collaborate with stakeholders, including government departments, industry partners, and academic institutions.
• Apply water quality expertise to irrigation systems, including the assessment of water suitability for agricultural use and the impact of irrigation practices on soil and crop health

• PhD in Chemistry, Environmental Science, Water Science, Water Resource Management or related field with a strong focus on water chemistry, biogeochemistry, freshwater and aquatic science.
• Proven experience in research, scientific inquiry and investigation, analysis and data management, modelling.
• Scientific publication and knowledge dissemination record.
• Experience in analytical instrumentation (e.g., ICP-MS, GC-MS, HPLC).
• Knowledge of water quality standards, regulations, and monitoring frameworks.
• Record of research collaboration and partnerships.
• Proven ability to function successfully in cross-cutting disciplinary teams.
• Excellent communication skills, written and verbal.
• Proven track record of mentoring, supervising and training students.
• Experience with field work and acquiring samples.
• Experience in irrigation-related research or water quality monitoring for agricultural applications.
• Valid code B & EB Driver’s licence and driving experience.

Enquiries: Dr AT Grundling, Tel:

CLOSING DATE FOR APPLICATIONS: 17 SEPTEMBER 2025

A competitive remuneration package will be congruent with the scope, responsibilities and the stature of the position. The appointment will be subject to a positive security clearance (as well as competency and leadership assessments).  
Preference will be given to designated groups in terms of the ARC Employment Equity Plan. The Agricultural Research Council is an equal opportunity employer and is committed to the principles and processes of Employment Equity Act.
Applications accompanied by a covering letter, detailed CV with at least three recent (3) contactable referees, certified copies of certificates, supporting documents and a copy of driver’s license must be attached on the form. 
A SAQA evaluation report must accompany foreign qualifications. Incomplete applications will not be considered. Applicants who do not receive any response four (4) weeks after the closing date must regard their applications as unsuccessful. Permanent appointments are subject to six (6) months’ probation period. The organisation reserves the right not to appoint.

• Collaborate with the Data Science and Analytics team to support data-driven insights, measurement, monitoring, and decision-making.
• Apply advanced analytical techniques to develop predictive and prescriptive models that drive value across business functions.
• Work across the full data science lifecycle, from problem definition and business understanding to model development and deployment.
• Perform data preprocessing, feature engineering, hypothesis testing, and machine learning model training.
• Deploy models into production, monitor performance, and refine solutions to ensure continuous improvement and business impact.

• Bachelors Degree with Honours, Masters, or a Doctorate in quantitative disciplines, such as Actuarial Science, Statistics, Computer Science, Engineering, or Mathematics.
• Relevant professional certifications in data science and associated technologies (for example, Python, Azure, AWS, Spark, big data, machine learning, and cloud platforms).
• Minimum 5 years of practical experience leading or actively participating in data science projects.
• Strong command of Python machine learning libraries and tools (including NumPy, Pandas, Matplotlib, and SciPy) and experience using Jupyter notebooks.
• Advanced SQL capabilities and proven experience handling extensive datasets.
• Proven track record of leveraging machine learning methods to address practical challenges.
• Familiarity with Agile frameworks and experience collaborating in Agile teams.
• Demonstrated success in deploying data science models or data-driven solutions into production environments.

• Develop and deploy predictive modelling and machine learning solutions.
• Collaborate with stakeholders to define business challenges and identify analytical opportunities.
• Conduct data cleaning, transformation, feature engineering, and rigorous hypothesis testing.
• Work with engineering teams to build data pipelines and access large-scale structured and unstructured data.
• Translate data science solutions into practical business applications.
• Create impactful visualisations and reports to communicate insights to both technical and non-technical stakeholders.
• Monitor and refine models to ensure performance and business relevance over time.

• Minimum:
  • Honours, Masters, or PhD in a quantitative discipline (e.g. Actuarial Science, Mathematics, Computer Science, Engineering, and Statistics).
  • 56 years of hands-on experience in data science and analytics roles.
  • Strong Python and SQL proficiency, including libraries such as NumPy, Pandas, SciPy, and Matplotlib.
  • Experience working with Jupyter Notebooks and in Agile development environments.
  • Proven ability to operationalise machine learning models at scale.
• Preferred:
  • Familiarity with cloud platforms (e.g. Azure and AWS), Spark, and big data tools.
  • Professional certifications in data science and analytics technologies.
  • Experience with data visualisation tools such as Power BI, Tableau, or Kibana.
• Key Competencies:
  • Advanced analytical and problem-solving skills.
  • Strong communication skills, with the ability to explain technical concepts to diverse audiences.
  • Business acumen and the ability to align data solutions with strategic objectives.
  • Initiative, adaptability, and a strong sense of accountability.
  • Ability to work independently as well as collaboratively within cross-functional teams.

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