The posting
Job Description
MTN is undergoing a significant transformation to become a platform-led, data-powered, and AI-native enterprise. This journey is driven by the increasing demand for intelligent data products that are scalable, market-responsive, and rooted in strong data governance. MTN-i, as MTN Group’s A.I.-driven data & intelligence commercialization business, is tasked with accelerating value delivery from our owned and partner intelligence assets
Global Influences:
The global economy is undergoing rapid digital transformation, with AI and machine learning emerging as core differentiators for competitive advantage. Enterprises are embedding predictive intelligence into their operations, products, and customer experiences to enhance efficiency, agility, and revenue growth. Meanwhile, cloud-native analytics platforms, federated learning, and MLOps frameworks are standardising how AI is scaled across complex, multi-market organisations. Heightened focus on data ethics, fairness, and regulatory compliance is also shaping the design of AI systems. As governments tighten rules around data privacy, bias mitigation, and model explainability, organisations must ensure that AI is not only effective but also responsible and trustworthy.
Industry Drivers: In the telecommunications sector, predictive analytics has become central to driving value from large-scale, real-time data generated by mobile networks, customer usage, and behavioral patterns. Use cases such as churn prediction, next-best-offer recommendations, network anomaly detection, and location-based targeting are no longer aspirational , they are expected. As telcos evolve into techcos and platform businesses, the ability to productise and monetise AI capabilities across industries such as FMCG, Retail, finance, and public services becomes a critical growth lever. Additionally, as data monetisation becomes mainstream, clients are not just asking for raw data but for intelligent insights, predictive signals, and decision-ready outputs all of which require robust data science capacity.
Organisational Mandate: MTN-i is at the forefront of MTN Group’s transformation into a commercial value delivery engine that is data-powered and AI-native. The team is building a multi-OpCo data product ecosystem capable of scaling advanced analytics solutions across markets via high-value use cases. Within this context, the Product Owner plays a critical role in translating MTN-i’s vision into high-impact intelligence solutions while navigating a federated technology landscape, orchestrating hyper-agile delivery, and ensuring that MTN-i’s data products are competitive, compliant, and commercially viable. The Senior Product Owner will be responsible for the end-to-end creation, delivery and lifecycle management of MTN-i's data, AI and technology-enabled product portfolio. This is a high-impact product leadership role for an exceptional product thinker who can move seamlessly between customer problems, commercial opportunities, data, technology, AI, product architecture and execution. The successful candidate will take products from 0→1 and 1→n: identifying customer needs and unmet market opportunities, validating product-market fit, translating opportunities into compelling product propositions, defining technical requirements and architectures, leading cross-functional delivery, launching products into market, and continuously optimising them based on customer, commercial and operational performance. Organization Values: At MTN we believe that understanding our people’s needs and aspirations is key to creating experiences that delight you at work, every day. We are committed to fostering an environment where every member of our Y’ello Family is heard, understood, and empowered to live an inspired life. Our values keep us grounded and moving in the right direction. Most importantly, they keep us honest. It is not something we claim to be. It is in our DNA. As an organisation, we consider it our mission to create an exciting and rewarding place to work, where our people can be themselves, thrive in positivity and ignite their full potential. A workplace that boosts creativity and innovation, improves productivity, and ultimately drives meaningful results. A workplace that is built on relationships and achieving a purpose that is bigger than us. This is what we want you to experience with us! Our commitments go beyond an organisational promise. It is in our leadership and managerial ethos to meaningfully partner with our employees, customers, and stakeholders with a vision to realise our shared goals. Our values dubbed, LIVE Y’ello, are the cornerstone of our culture.
Lead with Care Can-do with Integrity Collaborate with Agility Serve with Respect Act with Inclusion
Responsibilities
Discover and Validate Customer Problems
• Conduct structured customer discovery across enterprise, government, financial services, FMCG, media, advertising, technology and other priority segments. • Identify unmet customer needs, pain points and emerging market opportunities. • Translate customer problems into clearly articulated product opportunities. • Develop hypotheses around customer value, willingness to pay, addressable market and competitive differentiation. • Lead customer interviews, design-thinking sessions, workshops and proof-of-concept engagements. • Build a business case and validate product-market fit before significant technology investment. • Develop compelling problem statements, value propositions and product hypotheses.
Define Product Vision and Strategy
• Develop product vision, strategy, roadmap and business cases that are rigorously interrogated and boad-ready. • Define target customer segments, use cases, propositions and monetisation models. • Determine the appropriate balance between build, buy, partner and integrate. • Define MVP scope and a disciplined path from MVP → product-market fit → scale. • Establish product success metrics, including adoption, revenue, margin, customer value, usage and retention. • Continuously assess market, technology and competitive developments to identify opportunities for new products and product extensions. Own Technical Product Definition • Define functional and non-functional product requirements. • Develop product requirements documents, user stories, acceptance criteria and product specifications. • Work with architects and engineering teams to define appropriate technical architectures. • Understand APIs, data platforms, cloud infrastructure, data pipelines, analytics platforms, machine learning and AI architectures sufficiently to challenge and guide technical decisions. • Ensure products are designed for scalability, security, interoperability and operational resilience. • Establish appropriate data structures, APIs, integration requirements and data flows. • Evaluate emerging technology against business requirements rather than adopting technology for its own sake.
Lead End-to-End Product Delivery
• Lead multidisciplinary product squads comprising technology, data science, engineering, UX, commercial, legal, risk, compliance, finance and operations. • Establish delivery plans, milestones, dependencies and critical-path activities. • Remove organisational and technical blockers. • Make timely product trade-offs between scope, cost, quality, speed and customer value. • Maintain rigorous product governance without creating unnecessary bureaucracy. • Own launch readiness and go-to-market coordination. • Ensure products transition effectively from development into operational ownership. • Remain accountable for the product throughout its lifecycle—not just until launch.
Product Commercialisation and Monetisation
• Translate technical capabilities into commercially viable propositions. • Define pricing, packaging, consumption models and monetisation mechanisms. • Work with sales and commercial teams to develop customer propositions and sales enablement. • Support strategic customer engagements and complex solution design. • Identify opportunities to cross-sell, upsell and create adjacent products. • Establish commercial KPIs and monitor performance post-launch. • Continuously optimise products to improve revenue, margin, customer value and scalability.
Data, Analytics and Advanced Technology
• Bring exceptional understanding of data-driven products. • Advertising & audience monetisation: audience segmentation, first-party data activation, digital advertising, AdTech/MarTech, measurement and attribution, audience intelligence, consent and privacy management. • Geospatial: location intelligence, GIS, mobility analytics, footfall and visitation analytics, geofencing, spatial modelling and location-based segmentation. • Credit & risk: credit scoring, alternative data, risk modelling, fraud detection, identity intelligence, decisioning engines and machine-learning models for risk. • Data products: data APIs, data marketplaces, data licensing, Analytics-as-a-Service, data clean rooms/privacy-enhancing technologies, data governance and data quality. • The candidate need not be the deepest technical expert in every domain, but must understand the technology sufficiently to challenge specialists, make trade-offs and translate technical capabilities into customer and commercial value.
AI Leadership and Technology Advisory
• Assess emerging AI technologies, models and platforms for commercial applicability. • Identify opportunities to embed AI into MTN-i products. • Evaluate LLMs, SLMs, generative AI, machine learning, predictive analytics, agentic AI, RAG and AI-enabled decisioning. • Understand trade-offs between proprietary frontier models, open-source models and locally deployed models. • Assess AI solutions against accuracy, latency, cost, privacy, security, explainability, regulatory and operational requirements. • Challenge AI and product proposals that do not have a credible business case. • Identify opportunities to use AI to create new products rather than simply automate existing processes. • Work with data science and engineering teams to establish appropriate model-development, testing, monitoring and governance approaches. • Advise MTN-i leadership on the strategic implications of emerging AI technologies.
Agile and Modern Ways of Working
• Establish empowered, outcome-oriented product squads. • Apply Agile, Lean Startup, Design Thinking and continuous discovery principles. • Use rapid experimentation and evidence-based decision making. • Maintain a prioritised product backlog linked directly to customer and commercial outcomes. • Use MVPs, prototypes and pilots to test assumptions rapidly. • Establish product discovery and delivery as continuous rather than sequential processes. • Create a culture of accountability, transparency, experimentation and learning. Compliance, Risk and Responsible Data Use • Ensure products comply with applicable privacy, data protection, telecommunications, financial-services, advertising and other regulatory requirements. • Embed privacy, security, responsible AI and data governance into product design from inception. • Work closely with Legal, Compliance, Risk, Information Security and Data Governance teams. • Ensure appropriate customer consent, data usage rights and data provenance. • Establish appropriate controls for AI model risk, bias, explainability and data security. • Balance speed of innovation with appropriate enterprise risk management.
Qualifications
Education:
• 4 year degree in Computer Science, Business, Product Management, or related field (Master’s preferred). Experience: • 5 – 8 years of relevant experience in product management, technology, data, digital platforms, consulting, fintech, telecommunications, AdTech or related environments. • Proven track record of taking complex products from concept/vision through customer validation, development, launch and scale. • Demonstrated 0→1 product development experience. • Experience leading multidisciplinary technology and business teams without relying solely on formal reporting lines. • Strong technical understanding of modern data and technology architectures. • Significant experience in one or more of: advertising/audience monetisation, geospatial/location intelligence, credit scoring, risk/fraud, AI/machine learning, or API/platform businesses. • Demonstrated commercial understanding of how technology products create and capture value. • Strong experience with Agile product development and modern product operating models. • Demonstrated ability to work with senior executives, customers and technical specialists. • Strong understanding of data privacy, security, governance and regulatory requirements. • Advanced analytical and problem-solving capability. • Strong AI literacy and demonstrated ability to assess AI technologies and their business applicability.
Competencies:
• Product thinking: ability to identify the right problem before building the solution • Technical depth: able to challenge engineers and architects credibly • Commercial thinking: understands how a product becomes revenue and margin • Analytical problem solving: ability to break ambiguous problems into structured, testable hypotheses • Leadership: mobilise people across organisational boundaries • AI fluency: distinguish genuine AI opportunity from hype
Personal Attributes
• Exceptional intellectual curiosity • Highly structured thinker • Entrepreneurial and commercially minded • Comfortable with ambiguity • Bias toward action and experimentation • Customer obsessed • High ownership and accountability • Strong executive presence • Excellent written and verbal communication • Able to simplify highly complex concepts • Comfortable challenging conventional thinking • High standards for quality and execution • Low ego; highly collaborative • Builder rather than administrator
