Senior Data Scientist, Physical AI & Infrastructure ML

Sand Tech Holdings Limited; South Africa; Remote; ZAR 700,000 - 1,200,000; Full time

Job summary

Sand Technologies is seeking a Senior Data Scientist to join our growing data science team. You will solve complex business problems using advanced data analysis and machine learning, driving data‑driven decision making for our organisation and clients.

The ideal candidate will have a strong background in statistics and ML with a proven track record of delivering scalable, production‑ready solutions and experience moving models into production environments.

Qualifications

• 5+ years of applied data science experience in water, wastewater, utilities, or smart infrastructure environments.
• Proven ability to deploy ML solutions into production, including data pipelines and monitoring.

Responsibilities

• Conduct independent and collaborative research to develop data science and ML models.
• Apply data science and ML models to business problems and ensure integration into scalable products and services.
• Communicate results and impact to technical and non-technical stakeholders.
• Perform cutting-edge research in Physical AI at the intersection of engineering models and AI.
• Mentor junior data scientists and foster a culture of continuous improvement and innovation.
• Collaborate with cross-functional teams to drive data-driven decision making.

Skills

Time-series modeling

Anomaly detection

Forecasting

Geospatial analytics

Graph/network modeling

Production ML deployment

Data pipelines

MLOps

Model monitoring

Effective communication

Education

MSc in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field

PhD preferred

Tools

SCADA/AMI/IoT

Geospatial tooling

Job description

Sand Technologies is seeking a Senior Data Scientist to join our growing data science team. You will solve complex business problems using advanced data analysis and machine learning, driving data‑driven decision making for our organisation and clients.

The ideal candidate will have a strong background in statistics and ML with a proven track record of delivering scalable, production‑ready solutions and experience moving models into production environments.