Retail Data Scientist: ML & Analytics for Growth

Pick n Pay Retailers

South Africa

On-site

ZAR 900,000 - 1,200,000

Full time

5 days ago
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Job summary

Pick n Pay is seeking a talented Data Scientist to join the Analytics and Data Science stream within the Enterprise Data & Analytics division in South Africa. You will apply advanced analytics and ML to solve complex retail problems across customer experience, operations, and growth, leveraging AWS, Snowflake, and AI tools to deliver scalable insights.

You will work with cross-functional teams to transform data into actionable business recommendations, build predictive models, and communicate

Qualifications

  • Bachelor's degree in a quantitative field (Honours preferred).
  • 3–5 years of progressive data science experience.
  • Hands-on experience with Python and SQL for analysis and modelling.
  • Experience with cloud data platforms, preferably AWS and Snowflake.
  • Experience building and deploying ML models in business environments.

Responsibilities

  • Design, develop, and deploy ML models and analytical solutions for retail challenges.
  • Perform exploratory data analysis to identify trends and opportunities in large datasets.
  • Build predictive models to support merchandising, supply chain, marketing, and operations.
  • Develop customer segmentation and lifetime value models to improve targeting.
  • Apply statistical techniques to measure and optimize business outcomes.

Skills

Python
SQL
Power BI
Machine Learning
Data Visualization
AWS
Snowflake
Pandas/NumPy

Education

Bachelor's degree

Tools

Snowflake
AWS
Git

Job description

Pick n Pay is seeking a talented Data Scientist to join the Analytics and Data Science stream within the Enterprise Data & Analytics division in South Africa. You will apply advanced analytics and ML to solve complex retail problems across customer experience, operations, and growth, leveraging AWS, Snowflake, and AI tools to deliver scalable insights.

You will work with cross-functional teams to transform data into actionable business recommendations, build predictive models, and communicate

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