Azure Data Scientist

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)

• DP‑100 Azure Data Scientist Associate
  
• 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