Data ScientistPythonAzureMLOps (Contract) GautengHybrid ISB1403071

Our client is seeking an outcome-driven Senior Data Scientist who transforms business challenges into AI-enabled solutions through rigorous analysis machine learning expertise and collaborative platform engineering!

Design and deploy production-ready ML models using Python distributed data systems and cloud platforms while building robust data pipelines that support analytics and AI use cases!

The ideal candidate is a pragmatic data scientist who works comfortably close to data pipelines and production constraints excels at explaining models and uncertainty to business stakeholders brings strong foundations in statistics and machine learning with Python expertise (pandas scikit-learn PyTorch/TensorFlow) collaborates naturally with platform and observability teams and understands that trust transparency and governance are as important as model accuracy!

Senior data science with ML Python and distributed data systems

Hybrid and remote working flexibility with 1960 flexible annual hours

AI solutions role with MLOps and data engineering capabilities

Position: Contract: 01 June 2026 to 31 December 2026

Experience: Senior Level With Production Ml Experience

Commencement: 01 June 2026

Location: Hybrid: Midrand/Menlyn/Rosslyn/Home Office Rotation

Qualifications / Experience

• Is outcome-driven not model-driven
• Is comfortable working close to data pipelines and production constraints
• Can explain models and uncertainty to business stakeholders
• Collaborates naturally with platform AI engineering and observability teams
• Understands that trust transparency and governance are as important as accuracy

Essential Skills Requirements

• Data analysis exploration and feature engineering (EDA)
• Strong applied statistics and machine learning foundations
• Python-based data science and ML stack (e.g. pandas NumPy scikit-learn PyTorch / TensorFlow)
• Data engineering skills: ETL design batch and streaming data processing
• Experience with distributed data systems (e.g. Kafka Spark or equivalent)
• SQL and structured / semi-structured data querying
• Experiment design model evaluation and validation techniques
• Dashboarding reporting and data visualisation for insights and decision support
• Business problem translation and requirements understanding
• Version control and collaborative development (Git)

Advantageous Skills Requirements

• MLOps practices (model packaging deployment pipelines monitoring awareness)
• Data governance principles (data quality lineage ownership compliance awareness)
• Model evaluation performance tracking and drift detection concepts
• Cloud-based data and ML environments (Azure / AWS)
• Generative AI and LLM-based solution experience (preferred not essential)
• AI agent or advanced prompting familiarity
• Experience collaborating with observability and platform engineering teams
• Domain-specific knowledge aligned to business use cases

Role Requirements

• Translate business problems into data-driven and AI-enabled solutions
• Perform exploratory data analysis to uncover patterns issues and opportunities
• Design build and maintain data pipelines to support analytics and modelling use cases
• Develop train evaluate and iterate on machine learning and AI models
• Apply appropriate model evaluation techniques and define success metrics
• Support operational data workflows and resolve day-to-day data processing issues when required
• Produce clear dashboards reports and visualisations for stakeholders
• Communicate insights model behaviour and recommendations to both technical and business audiences
• Collaborate closely with data engineering AI platform and observability teams to productionise solutions
• Contribute to best practices around data quality governance and responsible use of AI

NB:

South African citizens/residents preferred. Valid work permit holders will be considered. By applying you consent to be added to the database and to receive updates until you unsubscribe. If you do not receive a response within 2 weeks please consider your application unsuccessful.

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