Data & Analytics Manager

Job Purpose

The Data and Analytics Manager is responsible for building and scaling the data analytics and data product capability that underpins commercial decision-making across Africa & Middle East. The role owns the transformation of complex multi-source data into accurate automated and scalable analytical solutions including dashboards models and data products that enable faster more reliable and forward-looking decisions.

Key Duties and Responsibilities

1. Data Product Ownership & Development (Own)

• Design build and own commercial and category data products including:
  • Market and category performance dashboards
  • Distribution and rate-of-sale tracking tools
  • Portfolio and mix performance analytics
• Translate business and insights requirements into scalable user-friendly and high-performance data products.
• Ensure data products are embedded into commercial planning and decision-making processes.
• Continuously improve tools based on user feedback adoption metrics and evolving business needs.

2. Data Integration Management & Quality (Own)

• Integrate and harmonise data from multiple sources including:
  • Data aggregators / retail scan data
  • Internal shipment and sales data
  • Distributor and customer data
• Build and maintain clean structured and standardised datasets across AME markets.
• Ensure data accuracy consistency and governance including KPI standardisation.
• Identify and resolve data issues ensuring high levels of data trust and reliability.

3. Advanced Analytics & Modelling (Own)

• Perform advanced analysis to identify:
  • Category and portfolio performance drivers
  • Channel and customer dynamics
  • Distribution and rate-of-sale relationships
• Develop and maintain analytical models and frameworks including:
  • Trend and performance decomposition
  • Forecasting and scenario modelling
  • Segmentation and clustering
• Generate predictive signals and forward-looking insights to support proactive decision-making.

4. Automation & Data Pipeline Enablement (Own)

• Automate recurring reporting and analytical processes to improve efficiency and scalability.
• Partner with Data Engineering teams to develop robust and scalable data pipelines.
• Reduce manual intervention and improve speed consistency and accessibility of data across markets.

5. Analytical Delivery & Support to Insights Function (Support)

• Partner closely with the Category Shopper & Commercial Insights Manager to:
  • Translate business questions into structured analytical outputs
  • Deliver high-quality datasets models and visualisations
• Provide iterative analytical support to refine insights and ensure accuracy and robustness of outputs.
• Ensure analytical outputs are clear structured and decision ready.

6. AI & Advanced Analytics Capability Building (Own)

• Leverage AI-enabled tools and modern analytics platforms to enhance insight generation and predictive capability.
• Support deployment of:
  • Machine learning models
  • Forecasting tools
  • Automated insight generation solutions
• Identify opportunities to embed AI and advanced analytics into commercial processes.

7. Data Governance & Best Practices (Own)

• Ensure compliance with data governance frameworks and policies.
• Standardise data definitions metrics and reporting structures across AME.
• Document data sources methodologies and analytical processes.
• Promote best practices in data management analytics and reporting.

8. Success Metrics (KPIs)

Data Quality & Reliability

• Accuracy completeness and consistency of datasets
• Reduction in data discrepancies and errors

Data Product Adoption

• Usage and adoption of dashboards and data tools across markets
• Stakeholder satisfaction with accessibility and usability

Efficiency & Automation

• Reduction in manual reporting processes
• Increased automation and scalability of data workflows

Analytical Impact

• Quality depth and timeliness of analytical outputs
• Ability to support faster and more accurate decision-making

Transformation Impact

• Adoption of advanced analytics and AI capabilities
• Improved data-driven culture across commercial teams

Key Competencies

Knowledge Skills and Attributes

• Strong analytical capability with experience working on large complex datasets
• Advanced proficiency in SQL and Excel
• Strong experience in data modelling structuring and transformation
• Experience building interactive dashboards and data products (Power BI QlikView or similar)
• Experience in automation and data pipeline processes
• Ability to perform advanced analytics and modelling
• Strong attention to detail and focus on data accuracy
• Ability to collaborate across technical and business teams
• Experience with Python R or similar tools is advantageous

Qualifications and Experience

• Bachelors degree in Data Science Statistics Mathematics Economics Computer Science or related field
• 58 years experience in Data Analytics Business Intelligence or Commercial Analytics
• Experience working with multiple data sources and large datasets
• Experience with data visualisation tools (Power BI QlikView or similar)
• Experience in FMCG retail or beverage industry is advantageous
• Experience working across multi-market or regional environments preferred

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