About the position
Role Summary
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, and
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.
Requirements
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, crossvalidation
Git basics - code review and collaboration
Experience turning raw data into actionable insights through advanced modelling
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.
Key Responsibilities
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.
Closing date: 09 January 2025
