Data Scientist

Pick n Pay Retailers; South Africa; On-site; ZAR 900,000 - 1,200,000; Full time

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

It's fun to work in a company where people truly BELIEVE in what they're doing!

Pick n Pay is seeking a talented Data Scientist to join our Analytics and Data Science stream within the Enterprise Data & Analytics division. This is an exciting opportunity to apply advanced analytics, machine learning and other AI-centric techniques to solve complex business problems across South Africa's retail landscape. Working alongside our Engineering & Architecture, Monetisation, and Reporting streams, you'll contribute to data-driven initiatives that directly impact customer experience, operational efficiency, and business growth. You'll leverage cutting-edge cloud technologies, including AWS, Snowflake, and AI-powered tools to deliver insights and solutions at scale.

Minimum Qualifications

Bachelor's degree (Honours preferred) in one of the following fields: Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, Engineering (with quantitative focus), Physics or other quantitative sciences.

Experience Required

• 3-5 years of progressive experience in data science, analytics, or related roles
• Proven track record of delivering end-to-end data science projects from problem definition through to production deployment
• Hands‑on experience with Python and SQL for data analysis and modelling
• Experience working with cloud data platforms, preferably AWS and Snowflake
• Demonstrated ability to work with large, complex datasets
• Experience building and deploying machine learning models in business environments
• Experience in retail, FMCG, or consumer-facing industries is advantageous

Technical Skills (all are not mandatory, this is a guideline)

• Core: Python (pandas, scikit-learn, numpy), SQL, statistical modelling, machine learning
• Cloud & Data Platforms: AWS services (S3, Glue, or similar), Snowflake (required)
• AI/ML Tools: Snowflake Cortex, Snowflake AI, or similar cloud-native ML platforms
• Visualisation: Power BI (required), experience translating data into business insights
• Data Engineering: Basic ETL/ELT concepts, data pipeline development, data quality practices
• Version Control: Git or similar

Competencies

• Strong problem‑solving skills with the ability to break down complex business challenges
• Excellent communication skills – able to explain technical concepts to non‑technical audiences
• Self‑motivated with the ability to work independently and collaboratively
• Curious mindset with a willingness to learn new tools and techniques
• Strong attention to detail and commitment to quality
• Ability to manage multiple priorities in a fast‑paced environment

Key Responsibilities

• Analytics & Modelling: Design, develop, and deploy machine learning models and analytical solutions addressing retail business challenges such as forecasting, customer lifetime value, customer churn prediction, pricing optimisation, and promotional effectiveness
• Conduct exploratory data analysis to identify trends, patterns, and opportunities across large-scale retail datasets
• Build predictive models to support decision‑making across merchandising, supply chain, marketing, and operations
• Develop customer segmentation and lifetime value models to enhance targeting and personalisation strategies
• Apply statistical techniques to measure and optimise business outcomes

Technical Delivery

• Extract, transform, and prepare data from multiple sources using Snowflake, AWS services, and other data platforms
• Implement scalable data pipelines and workflows to support analytics and machine learning use cases
• Leverage Snowflake Cortex and Snowflake AI capabilities to accelerate model development and deployment
• Write and document clean, efficient code in Python, SQL, and other relevant languages
• Perform basic data engineering tasks to support analytics workflows, including data quality checks and schema design

Visualisation & Communication

• Create compelling dashboards and visualisations in Power BI to communicate insights to technical and non-technical stakeholders
• Translate complex analytical findings into clear, actionable business recommendationsPresent findings to senior leadership and cross‑functional teams
• Document methodologies, models, and processes to ensure reproducibility and knowledge sharing

Collaboration & Innovation

• Partner with data product managers and business stakeholders to understand requirements and frame problems suitable for data science solutions
• Collaborate with data engineers, architects, and other analysts to deliver end‑to‑end solutions
• Stay current with emerging techniques in data science, machine learning, and retail analytics
• Contribute to the development of best practices and standards within the Analytics and Data Science team

Closing Date

17 September 2026

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Discover who we are

At Pick n Pay, we are more than just a retailer; we are an organisation of dedicated people committed to creating an exceptional shopping experience for our customers and an enriching, vibrant work environment for our employees. Founded in 1967, Pick n Pay is one of the largest retail chains in South Africa, serving millions of customers across the African continent. Our reputation is built upon our commitment to offering customers the best in quality, and value.

Our Mission

We serve with our hearts, we create a great place to be and With our minds, we create an excellent place to shop

Our Values

• Passion for our Customers: We are passionate about our customers and will fight for their rights. Our customers are our priority, and their satisfaction is our success.
• Respect and Care: We care for and respect each other. We value our team's diversity and treat each other with kindness and understanding.
• Personal Growth and Opportunity: We foster personal growth and opportunities. We believe in empowering our employees, providing opportunities for learning and advancement.
• Leadership and Innovation: We nurture leadership and vision, and reward innovation. We encourage our employees to be leaders in their roles and think outside the box.
• Honesty and Integrity: We live by honesty and integrity. We operate with transparency and trustworthiness in all our interactions.
• Community Support: We support and participate in our communities. We believe in making a positive impact and giving back to our communities.
• Individual Responsibility: We take individual responsibility. We are responsible for our actions and decisions.
• Accountability: We hold ourselves responsible for delivering on our commitments to our customers, each other, and our business.

Why Pick n Pay?

At Pick n Pay, our strength lies in our people. We strive to be the employer of choice, attracting and retaining the best talent in the industry. We create a work environment that fosters growth, celebrates achievements, and values individual contributions. Here, your work will be meaningful, recognized, and rewarded. Experience the joy of being part of Pick n Pay. Let's shape the future of retail in Africa together. View our career opportunities.