Retail Data Scientist: ML & Analytics Innovator

Pick n Pay; Cape Town; On-site; ZAR 700,000 - 900,000; Full time

Job summary

Pick n Pay is seeking a talented Data Scientist to join our Analytics and Data Science stream within the Enterprise Data & Analytics division. Apply advanced analytics and AI techniques to solve complex business problems across South Africa's retail landscape, leveraging AWS, Snowflake, and Power BI to deliver scalable insights.

The role focuses on forecasting, customer lifetime value, churn prediction, pricing optimisation, and promotional effectiveness, with end-to-end project delivery and

Qualifications

• Bachelor's degree (Honours preferred) in Data Science, Statistics, Mathematics, Actuarial Science, CS, Engineering (quantitative), Physics or other quantitative sciences.
• 3-5 years of progressive data science/analytics experience with end-to-end project delivery.
• Hands-on Python and SQL for data analysis and modelling; cloud platforms like AWS and Snowflake.

Responsibilities

• Design, develop, and deploy machine learning models addressing retail business challenges.
• Conduct exploratory data analysis to identify trends across large datasets.
• Build predictive models to support merchandising, supply chain, marketing, and operations.
• Develop customer segmentation and lifetime value models for targeting and personalization.
• Apply statistical techniques to measure and optimise business outcomes.

Skills

Python

SQL

Statistical modelling

Machine learning

Problem solving

Education

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

Tools

AWS

Snowflake

Power BI

Git

ETL/ELT

Job description

Pick n Pay is seeking a talented Data Scientist to join our Analytics and Data Science stream within the Enterprise Data & Analytics division. Apply advanced analytics and AI techniques to solve complex business problems across South Africa's retail landscape, leveraging AWS, Snowflake, and Power BI to deliver scalable insights.

The role focuses on forecasting, customer lifetime value, churn prediction, pricing optimisation, and promotional effectiveness, with end-to-end project delivery and