Retail Data Science Engineer: ML & Pipelines

Headhunters; Centurion; On-site; ZAR 670,000 - 1,004,000; Full time

Job summary

Headhunters is seeking a Data Science Developer (Retail) to design scalable data architectures and deliver ML-driven analytics. You will build robust data pipelines, deploy ML models, and collaborate with multiple stakeholders to translate business challenges into practical data solutions.

The role requires 3+ years in data science or analytics engineering, with advanced SQL, Python and Power BI skills, and an ability to prototype production-ready analytics within a retail context.

Qualifications

• BSc Honours or MSc in a related field preferred.
• Postgraduate qualification advantageous.
• Very strong SQL, Python and Power BI skills.
• Experience designing data architectures and pipelines.
• Proven ML/analytics production experience.

Responsibilities

• Design and improve data architectures for analytics and ML delivery.
• Build, optimise and maintain data pipelines from multiple sources.
• Develop, deploy and maintain ML models and analytical solutions.
• Collaborate with business and production stakeholders to deliver data solutions.
• Investigate new data sources and technologies for commercial opportunities.
• Prototype new data-driven solutions and translate business challenges into technical ones.
• Support and improve existing predictive models and decision-support tools.
• Contribute to code quality, documentation and deployment processes.
• Provide input into technical direction and architecture decisions.
• Share knowledge through coaching, presentations and updates.
• Estimate work, prioritise tasks and deliver on deadlines.

Skills

SQL

Python

Power BI

Data architecture

ML engineering

ETL/ELT

Agile

Stakeholder management

Team collaboration

Communication

Education

BSc Honours / MSc

Tools

Power BI

Job description

Headhunters is seeking a Data Science Developer (Retail) to design scalable data architectures and deliver ML-driven analytics. You will build robust data pipelines, deploy ML models, and collaborate with multiple stakeholders to translate business challenges into practical data solutions.

The role requires 3+ years in data science or analytics engineering, with advanced SQL, Python and Power BI skills, and an ability to prototype production-ready analytics within a retail context.