Big Data & Special CVM Projects Specialist
About the role
Big Data & Special CVM Projects Specialist Posting Country: Tanzania, United Republic of Date Posted: 4 Nov 2026 Full Time / Part Time: Full Time Contract Type: Permanent At Vodafone, we’re working hard to build a better future. A more connected, inclusive and sustainable world. As a dynamic global community, it's our human spirit, together with technology, that empowers us to achieve this. We challenge and innovate in order to connect people, businesses, and communities across the world. Delighting our customers and earning their loyalty drive us, and we experiment, learn fast and get it done, together. With us, you can be truly be yourself and belong, share inspiration, embrace new opportunities, thrive, and make a real difference. Join Us Role purpose: The Big Data & Special CVM Projects Specialist is responsible for leveraging advanced analytics, machine learning, and customer intelligence to drive sustainable customer and revenue growth across the M Pesa business. The role develops and operationalizes data-driven CVM strategies that improve customer acquisition, engagement, retention, product penetration, and customer lifetime value. The role is accountable for: • Co-creating and deploying advanced machine learning and artificial intelligence solutions that drive revenue growth, cost optimization, customer retention, and enhanced customer experience. • Developing big data monetization propositions and managing their end-to-end execution to unlock commercial value from customer data and behavioral insights. • Delivering actionable customer insights, predictive analytics, and segmentation strategies that support M-Pesa objectives, commercial targets, and business decision-making. • Designing and optimizing personalized customer lifecycle campaigns, including acquisition, activation, retention, reactivation, cross-sell, and upsell initiatives. • Driving customer value enhancement through time to action, causal inference, difference in difference propensity modelling, churn prediction and customer journey optimization initiatives. • Measuring and improving campaign effectiveness through Causal Inferences, advanced analytics, experimentation, and continuous optimization of customer engagement strategies. • Promoting effective data governance, data quality, and responsible use of customer information while ensuring compliance with regulatory and privacy requirements. Key accountabilities and decision ownersh