Azure Data Scientist: Build & Deploy Scalable ML on Azure

Amidel; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

Amidel seeks an experienced Intermediate/Senior Azure Data Scientist to drive ML model development and deployment on Microsoft Azure for diverse client engagements.

The role emphasizes Azure ML, Synapse, Databricks, and data engineering, with emphasis on production-grade pipelines and responsible AI practices. Collaboration across teams and stakeholders is essential to translate business use cases into AI solutions.

Qualifications

• 5+ years of experience in data science, analytics, or AI/ML solution development.
• 3+ years working on Microsoft Azure-based data science platforms.
• Bachelor’s degree in data science, CS, statistics, or mathematics (or related field).
• Azure AI Engineer Associate or Azure Solutions Architect Expert is advantageous.

Responsibilities

• Design, build, and deploy scalable ML models on Azure.
• Work with Azure ML to train, test, and operationalize models.
• Ingest, transform, and feature engineer data using Azure Data Factory, Synapse, and Databricks.
• Collaborate with data engineers to develop robust data pipelines for modelling.
• Select and tune ML algorithms and evaluation metrics for business problems.
• Integrate ML models into business apps via APIs or embedded services.
• Ensure secure, reproducible ML workflows and ML lifecycle management.
• Maintain responsible AI practices for fairness and transparency.
• Create interactive Power BI dashboards to visualize predictive insights.

Skills

Python

ML deployment

Azure ML

Data engineering

Power BI

Cross-functional

Statistics

Education

Bachelor’s degree in data science / CS / statistics / math

Azure AI Engineer Associate

Azure Solutions Architect Expert

Tools

Azure ML

Azure Synapse

Databricks

Azure Data Factory

Data Lake

APIs

Job description

Amidel seeks an experienced Intermediate/Senior Azure Data Scientist to drive ML model development and deployment on Microsoft Azure for diverse client engagements.

The role emphasizes Azure ML, Synapse, Databricks, and data engineering, with emphasis on production-grade pipelines and responsible AI practices. Collaboration across teams and stakeholders is essential to translate business use cases into AI solutions.