Data Scientist

Pick n Pay is hiring a Data Scientist in the Analytics and Data Science stream of Enterprise Data & Analytics. The role uses advanced analytics, machine learning and other AI methods on retail problems, working with Engineering & Architecture, Monetisation and Reporting. Work includes AWS, Snowflake and AI tools.

Minimum qualifications
Bachelor’s degree (Honours preferred) in one of:

• Data Science
• Statistics
• Mathematics
• Actuarial Science
• Computer Science
• Engineering with a quantitative focus
• Physics or another quantitative science

Experience

• 3–5 years in data science, analytics or a related role
• End-to-end data science projects, from problem definition to production
• Hands-on Python and SQL for analysis and modelling
• Cloud data platforms, preferably AWS and Snowflake
• Large, complex datasets
• Building and deploying machine learning models in a business setting
• Retail, FMCG or consumer-facing experience is an advantage

Technical skills (guideline — not all required)

• Core: Python (pandas, scikit-learn, NumPy), SQL, statistical modelling, machine learning
• Cloud and data: AWS (S3, Glue or similar); Snowflake required
• AI/ML: Snowflake Cortex, Snowflake AI or similar cloud ML tools
• Visualisation: Power BI required
• Data engineering: basic ETL/ELT, pipelines, data quality
• Version control: Git or similar

Competencies

• Problem-solving
• Ability to explain technical work to non-technical people
• Self-motivated; able to work alone and in a team
• Curious and willing to learn new tools
• Attention to detail
• Ability to handle several priorities in a fast-paced environment

Key responsibilities

Analytics and modelling

• Design, build and deploy ML and analytics solutions for retail problems (forecasting, customer lifetime value, churn, pricing, promotions)
• Explore large retail datasets for trends and opportunities
• Build predictive models for merchandising, supply chain, marketing and operations
• Develop customer segmentation and lifetime-value models
• Use statistics to measure and improve business results

Technical delivery

• Extract, transform and prepare data in Snowflake, AWS and other platforms
• Implement scalable pipelines and workflows
• Use Snowflake Cortex and Snowflake AI where relevant
• Write and document clean Python, SQL and related code
• Do basic data engineering, including quality checks and schema design

Visualisation and communication

• Build Power BI dashboards
• Turn findings into clear recommendations
• Present to senior leaders and other teams
• Document methods, models and processes

Collaboration

• Work with data product managers and business stakeholders
• Work with data engineers, architects and analysts
• Keep up with data science, ML and retail analytics
• Help set team standards and practices