Data Analyst, Shopper Insights

About the role

Mondelēz International's Sub-Saharan Africa Business Unit (Southern Africa, West Africa and the Rest of Africa) is looking for a Data Analyst, Shopper Insights. You will support and execute the shopper insight capability, driving shopper-centric plans across shelf, secondary displays and hot zones, and activating insights on cross-category activations with internal stakeholders.

Key responsibilities

• Own the end-to-end alignment of PRA-data aggregator (Spot 2 D) feeds with country distributor data, resolve mismatches and build an auditable mapping framework before the incentive-on-IMS transition.
• Act as the main data contact with distributor data managers across CEA markets, understand each country's nuances and prioritise data work at the distributor end.
• Produce and maintain coverage numbers by country, channel and retail environment, highlighting white spaces and growth opportunities.
• Support DFC files: validate formulas, check for gaps and opportunities, and keep the file accurate and current.
• Deliver clear, accurate commercial reports for sales and market management teams.
• Generate growth opportunities in the retail environment, optimise business through data, track and learn, and build research plans and recommendations for country-specific knowledge gaps.
• Develop insights on general grocery shopping behaviour (trip missions, channel habits) and on drivers of in-store performance, shelf layout, assortment, promotion and pricing.

Required profile

• Diploma or degree; 3-5 years in a data or commercial analytics role, ideally in FMCG and traditional trade.
• Experience in market research (FMCG/CPG manufacturer or major retailer) and consumer/shopper research.
• Strong knowledge of the retail environment and the 4 C's.
• Experience with data aggregators (PRA, Nielsen, IRI) and coverage/numeric distribution metrics is a strong plus.
• Willingness to work independently in a remote team.

Required skills

• Excellent Excel / spreadsheet skills, including formulas, data validation and large-file management.
• Go-to-market models, distributor ecosystems and in-market sales data flows.
• Strong analytical skills, attention to detail and good communication and presentation skills.