Senior Manager Analytics at Pick n Pay Stores Limited

• To lead the analytics and data science function, delivering advanced analytical insights, predictive models, and other AI/ML solutions that drive commercial impact, operational efficiency, and customer engagement for Pick n Pay.

This role is accountable for:

• Building and managing a high-performing team of analysts and data scientists.
• Overseeing the analytics and data science roadmap.
• Implementing a demand process for analytics and data science requests.
• Ensuring the effective embedding of insights into decision-making across the organisation.
• The Senior Manager works closely with business stakeholders to identify opportunities, scope analytical projects, and measure value delivered.
• Minimum: Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field.
• Preferred: Master’s or PhD in a quantitative discipline; certifications in AI/ML or advanced analytics tools (e.g. Python, R).
• Minimum: 8+ years in analytics or data science, with at least 3 years in a leadership role.

Preferred:

• Retail/FMCG analytics experience
• Proven delivery of predictive and prescriptive analytics solutions at scale
• Experience managing hybrid teams and multiple concurrent projects
• Strong commercial acumen
• Proficiency in analytics tools and technologies including Snowflake, Microsoft SQL Server, Python, Power BI, BigQuery, Redshift or comparable platforms.
• Working knowledge of statistical modelling, machine learning, and advanced analytics foundations such as regression, decision trees, random forests, gradient boosting, clustering, feature engineering, cross-validation
• Git basics – code review and collaboration
• Experience turning raw data into actionable insights through advanced modelling.

Key Responsibilities

• Define and execute the analytics & data science strategy, aligned to enterprise data objectives and business priorities.
• Lead the development, deployment, and maintenance of predictive models (price elasticity and optimization, promo effectiveness, demand forecasting), customer segmentation and recommendation systems to enable proactive decision making across the organization.
• Lead experimentation practices such as A/B testing, control group design and causal inference to validate
  impact before scaling solutions
• Ensure ethical, transparent, and privacy-compliant use of AI/ML techniques.
• Partner with business units to embed insights into decision-making and measure impact on KPIs.
• Collaborate with Data Engineering and Reporting teams to ensure timely access to quality data for analysis and model development
• Define and oversee end-to-end data science project lifecycles — from problem framing to deployment.
• Review methodologies, model designs, and analysis approaches for technical soundness
• Ensure reproducibility, proper documentation, and adherence to best practices
• Plan, prioritize, communicate, and coordinate projects and resources
• Promote data and AI literacy and analytical capability across the organization.
• Stay abreast of emerging analytics and AI/ML trends, technologies, and best practices, and apply them where relevant.
• Manage external partnerships and vendor relationships for advanced analytics tools and platforms.
• Lead, mentor, and develop a skilled team of analysts and data scientists.

Competencies

• Cognitive: Strategic thinking, Analytical capability, Problem solving, Judgement & decision-making.
• Personal: Drive, Curiosity, Resilience, Accountability.
• Interpersonal: Stakeholder engagement, Collaboration, Influence.
• Communication: Data storytelling, Executive presentation, Negotiation.
• Functional: Advanced analytics, Data science, Machine learning, AI, Statistical modelling, Data visualisation, Experiment design.
• Leadership: Team leadership, Capability building, Change management.

End Date: December 24, 2025