Azure Data Scientist
Summary
Build and deploy machine learning models on Azure using Python, Azure ML, and Databricks to deliver data-driven insights and predictive analytics for business stakeholders.
Johannesburg, South Africa | Posted on 02/13/2026
The Azure Data Scientist will be responsible for developing machine learning models, applying advanced analytics techniques, and delivering data-driven insights using Azure-based tooling. This role requires strong analytical capability, statistical modelling expertise, and hands‑on experience with Azure ML ecosystems.
Key Responsibilities
- Build, train, validate, and deploy machine learning models on Azure (Azure ML, Databricks).
- Perform data exploration, feature engineering, statistical modelling , and predictive analytics.
- Collaborate with data engineers to ensure availability of high-quality training data.
- Work with business stakeholders to translate business problems into ML solutions.
- Develop automated ML workflows using Azure ML Pipelines , MLOps practices, and versioning strategies.
- Monitor model performance, drift, and quality; implement continuous improvement processes.
- Present insights, findings, and recommendations to technical and non-technical audiences.
Required Technical Skills
- Proficiency in Python (pandas, scikit-learn, NumPy, PyTorch/TensorFlow optional).
- Experience with Azure Machine Learning , Databricks , Synapse , and associated ML tooling.
- Strong statistical and mathematical modelling skills.
- Experience with MLOps , Azure DevOps, Git version control, and CI/CD for ML.
- Familiarity with distributed ML and big data frameworks (Spark ML).
- Ability to work with structured and unstructured datasets.
Qualifications & Certifications (Preferred)
- Other relevant Azure or ML certifications (Databricks ML, TensorFlow Developer, etc.).
- Degree in Data Science, Applied Mathematics, Computer Science, Statistics, or equivalent.
Experience
- 3–5+ years in machine learning, AI, data science, or advanced analytics.
- Proven experience delivering production-ready ML models in cloud environments.
Location & Working Model
- Location: Johannesburg (Hybrid working model)
- Ways of Working: Standard SAST business hours
- Candidate: Preferably a South African Citizen or Permanent Resident