Azure Data Scientist

3 days ago


Johannesburg Gauteng South Africa Amidel Full time R500 000 - R1 200 000 per year

Amidel is an Information Technology and Business Consulting Company that provides highly specialised solutions to large and small enterprises in both the private and public sectors. We seek a highly motivated and experienced Intermediate/Senior Azure Data Scientist. The ideal candidate should have a strong background in machine learning, data engineering, and AI model deployment using Microsoft Azure technologies.

This role presents a dynamic opportunity to work on impactful data-driven solutions with leading organisations in sectors such as finance, healthcare, and public service. The candidate should ideally hold the Microsoft Certified: Azure Data Scientist Associate certification.

Job Family:

  • Data Science / Artificial Intelligence / Cloud Analytics

Minimum Experience:

  •  5 Years working in data science, analytics, or AI/ML solution development.
  • 3 Years working on Microsoft Azure-based data science platforms.

Qualification:

  •  Bachelor's degree in data science, Computer Science, Statistics, Mathematics, or a related field
  • Advantageous: Microsoft Certified: Azure AI Engineer Associate or Azure Solutions Architect Expert

Contract Type:

Permanent or Fixed-Term

DUTIES AND RESPONSIBILITIES 

Responsibilities vary by client engagement and may include:

  • Designing, building, and deploying scalable machine learning models on Azure
  • Working with Azure Machine Learning (Azure ML) to train, test, and operationalize AI models.
  • Performing data ingestion, transformation, and feature engineering using Azure Data Factory, Synapse Analytics, and Databricks
  • Collaborating with data engineers to develop robust data pipelines and prepare data for modelling
  • Selecting and fine-tuning appropriate ML algorithms and evaluation metrics for different business problems
  • Integrating machine learning models into business applications via APIs or embedded services
  • Enabling secure and reproducible ML workflows using ML pipelines and automated ML (AutoML)
  • Leveraging responsible AI practices to ensure fairness, accountability, and transparency in models.
  • Creating interactive reports and dashboards using Power BI to visualise predictive insights.
  • Working with large datasets from diverse sources (structured, semi-structured, unstructured)
  • Engaging with business stakeholders to translate use cases into AI solutions.
  • Supporting model monitoring, drift detection, and lifecycle management in production environments
  • Documenting processes and sharing knowledge with teams and clients

COMPETENCIES

  • Proven experience building and deploying machine learning models in cloud environments.
  • Proficiency in Python and common ML/data libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
  • Experience using Azure ML, Synapse Analytics, and Data Lake for data science workflows.
  • Knowledge of data pre-processing, feature engineering, and model validation techniques.
  • Familiarity with MLOps principles and automated ML lifecycle management.
  • Strong understanding of statistics, data wrangling, and algorithm optimisation.
  • Experience working with both structured and unstructured data (e.g., text, images, sensor data).
  • Hands-on experience with data integration tools such as Azure Data Factory and Databricks.
  • Microsoft Certified: Azure Data Scientist Associate (must have or in progress).
  • Excellent communication and presentation skills for both technical and non-technical audiences.
  • Ability to work in cross-functional teams and translate complex problems into actionable solutions.
  • Financial or enterprise industry experience is an advantage.
  • Exposure to hybrid cloud data environments is a plus.

If you are passionate about solving real-world problems through data, machine learning, and AI innovation on the Microsoft Azure platform, we encourage you to apply. This is a unique opportunity to shape intelligent solutions and accelerate digital transformation across industries while growing your expertise in the Microsoft data ecosystem.


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