Data Scientist & ML Product Architect

Edge Executives; Centurion; On-site; ZAR 600,000 - 900,000; Full time

Job summary

Edge Executives is seeking a mid-level Data Scientist/Architect to design and implement scalable data architectures and analytics products. The role blends data science, ML, data engineering and product development to deliver measurable commercial value.

You will work across data architecture, pipelines and production ML in a collaborative, client-focused setting. The successful candidate will build predictive models, maintain data products in production, and collaborate with cross-functional

Qualifications

• Minimum 3 years in data science or related field.
• BSc Honours or MSc preferred.
• Proficiency in SQL, Python and Power BI.
• Experience in building robust, scalable data pipelines.
• Production deployment of ML models or analytics solutions.
• Strong statistical and ML knowledge with business application.
• Experience with data architecture and ETL/ELT processes.

Responsibilities

• Design data architectures to support analytics and scalable product delivery.
• Build and maintain robust data pipelines from multiple sources.
• Develop and deploy ML models and analytical solutions in production.
• Translate business challenges into practical technical solutions.
• Collaborate with internal and external stakeholders in Agile environment.
• Contribute to architecture decisions and continuous improvement.

Skills

SQL

Python

Power BI

Data pipelines

Machine learning

Statistical methods

Data architecture

Production ML deployment

Agile

Data science engineering

Education

BSc Honours or MSc in Statistics/Math/CS/Data Science/Engineering

Tools

Git

Job description

Edge Executives is seeking a mid-level Data Scientist/Architect to design and implement scalable data architectures and analytics products. The role blends data science, ML, data engineering and product development to deliver measurable commercial value.

You will work across data architecture, pipelines and production ML in a collaborative, client-focused setting. The successful candidate will build predictive models, maintain data products in production, and collaborate with cross-functional