{"id":2702084,"url":"https://alion.io/job/mtn-group-senior-manager-product-owner-dataco","title":"Senior Manager - Product Owner.DataCo","company":{"id":57356,"name":"MTN Group","domain":"mtn.com","url":"https://alion.io/company/mtn-group","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":null},"role":"Product","role_family":"Product","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Roodepoort, South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":30000,"max_usd":67000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":4457},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Federated Learning","optional":false},{"name":"Machine Learning","optional":false},{"name":"MVP","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-10-16T07:06:36Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-03T04:03:02Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"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\nGlobal Influences:\nThe 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.\nHeightened 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.\nIndustry Drivers:\nIn 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.\nAdditionally, 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.\nOrganisational Mandate:\nMTN-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.\nWithin 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.\nThis 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.\nThe 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.\nOrganization 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.\nAs 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!\nOur 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.\nOur values dubbed, LIVE Y’ello, are the cornerstone of our culture.\nLead with Care\nCan-do with Integrity\nCollaborate with Agility\nServe with Respect\nAct with Inclusion\n Discover and Validate Customer Problems\nConduct structured customer discovery across enterprise, government, financial services, FMCG, media, advertising, technology and other priority segments.\nIdentify unmet customer needs, pain points and emerging market opportunities.\nTranslate customer problems into clearly articulated product opportunities.\nDevelop hypotheses around customer value, willingness to pay, addressable market and competitive differentiation.\nLead customer interviews, design-thinking sessions, workshops and proof-of-concept engagements.\nBuild a business case and validate product-market fit before significant technology investment.\nDevelop compelling problem statements, value propositions and product hypotheses.\nDefine Product Vision and Strategy\nDevelop product vision, strategy, roadmap and business cases that are rigorously interrogated and boad-ready.\nDefine target customer segments, use cases, propositions and monetisation models.\nDetermine the appropriate balance between build, buy, partner and integrate.\nDefine MVP scope and a disciplined path from MVP → product-market fit → scale.\nEstablish product success metrics, including adoption, revenue, margin, customer value, usage and retention.\nContinuously assess market, technology and competitive developments to identify opportunities for new products and product extensions.\nOwn Technical Product Definition\nDefine functional and non-functional product requirements.\nDevelop product requirements documents, user stories, acceptance criteria and product specifications.\nWork with architects and engineering teams to define appropriate technical architectures.\nUnderstand APIs, data platforms, cloud infrastructure, data pipelines, analytics platforms, machine learning and AI architectures sufficiently to challenge and guide technical decisions.\nEnsure products are designed for scalability, security, interoperability and operational resilience.\nEstablish appropriate data structures, APIs, integration requirements and data flows.\nEvaluate emerging technology against business requirements rather than adopting technology for its own sake.\nLead End-to-End Product Delivery\nLead multidisciplinary product squads comprising technology, data science, engineering, UX, commercial, legal, risk, compliance, finance and operations.\nEstablish delivery plans, milestones, dependencies and critical-path activities.\nRemove organisational and technical blockers.\nMake timely product trade-offs between scope, cost, quality, speed and customer value.\nMaintain rigorous product governance without creating unnecessary bureaucracy.\nOwn launch readiness and go-to-market coordination.\nEnsure products transition effectively from development into operational ownership.\nRemain accountable for the product throughout its lifecycle-not just until launch.\nProduct Commercialisation and Monetisation\nTranslate technical capabilities into commercially viable propositions.\nDefine pricing, packaging, consumption models and monetisation mechanisms.\nWork with sales and commercial teams to develop customer propositions and sales enablement.\nSupport strategic customer engagements and complex solution design.\nIdentify opportunities to cross-sell, upsell and create adjacent products.\nEstablish commercial KPIs and monitor performance post-launch.\nContinuously optimise products to improve revenue, margin, customer value and scalability.\nData, Analytics and Advanced Technology\nBring exceptional understanding of data-driven products.\nAdvertising & audience monetisation: audience segmentation, first-party data activation, digital advertising, AdTech/MarTech, measurement and attribution, audience intelligence, consent and privacy management.\nGeospatial: location intelligence, GIS, mobility analytics, footfall and visitation analytics, geofencing, spatial modelling and location-based segmentation.\nCredit & risk: credit scoring, alternative data, risk modelling, fraud detection, identity intelligence, decisioning engines and machine-learning models for risk.\nData products: data APIs, data marketplaces, data licensing, Analytics-as-a-Service, data clean rooms/privacy-enhancing technologies, data governance and data quality.\nThe 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.\nAI Leadership and Technology Advisory\nAssess emerging AI technologies, models and platforms for commercial applicability.\nIdentify opportunities to embed AI into MTN-i products.\nEvaluate LLMs, SLMs, generative AI, machine learning, predictive analytics, agentic AI, RAG and AI-enabled decisioning.\nUnderstand trade-offs between proprietary frontier models, open-source models and locally deployed models.\nAssess AI solutions against accuracy, latency, cost, privacy, security, explainability, regulatory and operational requirements.\nChallenge AI and product proposals that do not have a credible business case.\nIdentify opportunities to use AI to create new products rather than simply automate existing processes.\nWork with data science and engineering teams to establish appropriate model-development, testing, monitoring and governance approaches.\nAdvise MTN-i leadership on the strategic implications of emerging AI technologies.\nAgile and Modern Ways of Working\nEstablish empowered, outcome-oriented product squads.\nApply Agile, Lean Startup, Design Thinking and continuous discovery principles.\nUse rapid experimentation and evidence-based decision making.\nMaintain a prioritised product backlog linked directly to customer and commercial outcomes.\nUse MVPs, prototypes and pilots to test assumptions rapidly.\nEstablish product discovery and delivery as continuous rather than sequential processes.\nCreate a culture of accountability, transparency, experimentation and learning.\nCompliance, Risk and Responsible Data Use\nEnsure products comply with applicable privacy, data protection, telecommunications, financial-services, advertising and other regulatory requirements.\nEmbed privacy, security, responsible AI and data governance into product design from inception.\nWork closely with Legal, Compliance, Risk, Information Security and Data Governance teams.\nEnsure appropriate customer consent, data usage rights and data provenance.\nEstablish appropriate controls for AI model risk, bias, explainability and data security.\nBalance speed of innovation with appropriate enterprise risk management.\nEducation:\n4 year degree in Computer Science, Business, Product Management, or related field (Master’s preferred).\nExperience:\n5 - 8 years of relevant experience in product management, technology, data, digital platforms, consulting, fintech, telecommunications, AdTech or related environments.\nProven track record of taking complex products from concept/vision through customer validation, development, launch and scale.\nDemonstrated 0→1 product development experience.\nExperience leading multidisciplinary technology and business teams without relying solely on formal reporting lines.\nStrong technical understanding of modern data and technology architectures.\nSignificant 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