Retail Data Scientist: ML & Cloud Analytics

picknpay; Cape Town; On-site; ZAR 600,000 - 900,000; Full time

Job summary

Pick n Pay in South Africa is seeking a Data Scientist to join the Analytics and Data Science stream within the Enterprise Data & Analytics division. You will apply advanced analytics and machine learning to retail challenges across South Africa's retail landscape.

You will work with AWS, Snowflake, and Power BI to deliver scalable insights, collaborate with engineering, monetisation, and reporting streams, and translate data into actionable business decisions for customer experience and growth.

Qualifications

• Bachelor's degree (Honours preferred) in a quantitative field.
• 3–5 years of progressive data science and analytics experience.
• Hands-on with Python and SQL for analysis and modeling.
• Experience with cloud platforms, preferably AWS and Snowflake.
• Retail, FMCG, or consumer-facing experience is advantageous.
• Proficiency with Power BI and translating data into insights.

Responsibilities

• Design, develop, and deploy ML models addressing retail challenges.
• Conduct exploratory data analysis to uncover trends and opportunities.
• Build predictive models for merchandising, supply chain, and marketing.
• Develop customer segmentation and lifetime value models.
• Apply statistical techniques to measure and optimise outcomes.
• Translate findings into actionable business recommendations.

Skills

Python

SQL

Power BI

Machine learning

Statistical modelling

Data analysis

Problem solving

Education

Bachelor's degree (Honours preferred) in Data Science/Statistics/Mathematics/Actuarial Science/CS/Engineering/Physics

Tools

Snowflake

AWS

Git

Snowflake Cortex

Snowflake AI

ETL/ELT

Job description

Pick n Pay in South Africa is seeking a Data Scientist to join the Analytics and Data Science stream within the Enterprise Data & Analytics division. You will apply advanced analytics and machine learning to retail challenges across South Africa's retail landscape.

You will work with AWS, Snowflake, and Power BI to deliver scalable insights, collaborate with engineering, monetisation, and reporting streams, and translate data into actionable business decisions for customer experience and growth.