Location: Kempton Park
Position: Permanent

• Bachelor’s Degree in Computer Science, Engineering, or a related field

Experience:

• 1–3 years’ experience in a data science role
• Exposure to mining, mineral processing, or supply chain environments is preferred

Key Responsibilities:
Enterprise Data Integration

• Consolidate organizational data into unified, accessible architectures using modern warehousing/lakehouse methods

Business Intelligence Enablement

• Build and maintain analytics dashboards for departments such as Finance, Supply Chain, Customer Service, Engineering, and Projects

Applied Machine Learning

• Design and deploy models for predictive maintenance, anomaly detection, and RUL estimation

Stakeholder Engagement & Ad Hoc Analytics

• Work closely with stakeholders to solve business problems through data-driven solutions

Data Storytelling

• Translate complex analytical insights into impactful, actionable narratives for various audiences

Technical Proficiency
Data Engineering & Integration

• Microsoft Fabric (OneLake, Lakehouse, DW) – Advantageous
• ETL/ELT tools (Azure Data Factory, Synapse Pipelines)
• Dimensional modelling (Star/Snowflake schema)
• SQL (T-SQL, M code), Data Gateway knowledge
• PostgreSQL / SQL Server

Machine Learning & Analytics

• Python (required), R/Spark (beneficial)
• Time Series Forecasting (ARIMA, Prophet, LSTM)
• Predictive Maintenance Techniques
• Scikit-learn, Azure ML, Azure Functions/AKS

Business Intelligence

• Power BI (DAX, M code, dashboards)
• Root cause analysis, ad hoc reporting

Software & Cloud Development (Advantageous)

• REST APIs, Azure App Services
• Microservices and web-based ML integration

Supply Chain & Inventory Analytics (Advantageous)

• Inventory optimization, demand planning
• EOQ, reorder point, ABC analysis