Data Scientist
Job in
Stellenbosch, 7600, South Africa
Listed on 2026-01-26
Listing for:
Plus1X Solutions (Pty) Ltd
Contract
position Listed on 2026-01-26
Job specializations:
-
IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer
Job Description & How to Apply Below
Data Scientist - Contract (Hybrid - Stellenbosch)
Purpose Statement
To drive the AI strategy, ensuring the organization remains competitive in a dynamic landscape where data science is a key strategic differentiator. To design and implement predictive models and intelligent algorithms that enhance business performance and support improved decision-making.
Education
Minimum:
- Honours Degree in Data Science
Preferred:
- Masters Degree in Data Science
Knowledge and Experience
Minimum Requirements:
- Master’s degree or equivalent in a quantitative discipline or STEM field (e.g., Mathematics, Statistics, Engineering, Computer Science) with a focus on Machine Learning, plus 6 years of relevant experience.
Or - Honours Degree or equivalent with relevant technical qualifications, plus 8 years of relevant experience.
- Experience in data science, machine learning, and deploying developed solutions.
- Proficiency in business analysis and requirements gathering.
- Experience in reproducible coding, working with relational and non-relational databases, and at least one machine learning language.
- Experience working in cloud environments.
Ideal Requirements:
- Experience collaborating with multiple teams to deliver predictive models into a production environment.
- Proven ability in stakeholder management at Executive and senior management levels.
Knowledge
Minimum:
- Deep understanding of state-of-the-art and emerging principles and techniques in at least one discipline of data science (e.g., NLP, Deep Learning) and the ability to teach these to a wide technical audience.
- Strong grasp of the theory and application of machine learning models, with the ability to educate others.
- Familiarity with modern deep learning frameworks (Tensorflow, PyTorch, MXNet, etc).
- Best practices for data science.
- Ethical AI design principles.
Ideal:
- Understanding of the Data Science lifecycle and Data Product Life Cycle within an organization.
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