Executive Head: VSA Big Data, AI & IA at Vodafone Global Enterprise

Role Purpose/Business Unit:

• The Executive Head VSA Big Data, AI & IA: Lead Data Scientist is the principal technical authority for data science and AI within Vodacom South Africa. The role steers the design, build and scaled deployment of high-impact AI services across the VSA business, aligned to Vodacom’s three strategic AI impact pillars of Customer Experience (CX), Monetization and Productivity, and to our ambition of becoming an AI-native organisation by 2030.
• Operating solely within the Vodacom South Africa Big Data team, the incumbent acts as the lead technical expert and hands-on architect: identifying opportunities to make a commercial difference, leading the development of machine learning and AI initiatives end-to-end, and mentoring a high-performing team of data scientists and AI engineers. The ideal candidate is deeply versed in Customer Value Management (CVM) principles, real-time recommender systems, Generative and Agentic AI, and modern MLOps / LLMOps practice.
• Success in this role requires the ability to build trusted relationships with business stakeholders, translate complex datasets into strategic insight, and deliver business value in close partnership with technology, commercial and analytics teams across VSA.

Your responsibilities will include:

Technical Leadership

• Principal technical expert: act as the lead data scientist for Vodacom South Africa, identifying opportunities to make a commercial difference and leading the development of machine learning and AI initiatives to meet business requirements.
• AI vision and roadmap: set the technical vision, roadmap and delivery priorities for centrally built AI services across the VSA business, aligned to the Group AI strategy, the Vodafone Group GenAI framework and the Tech enablement strategy for AI.
• Insight translation: translate complex datasets into strategic insights, communicating simply to non-technical audiences and visualising results to create understanding and solution buy-in.
• Innovation agenda: identify new analytics and AI trends, evaluating and integrating emerging technologies, including agentic AI, multimodal models and real-time decisioning, to maintain Vodacom’s competitive advantage.
• Thought leadership: serve as a recognised expert in the community, mentoring and advising colleagues on statistical techniques, algorithms, data and responsible AI practice.

AI Services Design, Build & Reusability

• Reusable AI services: architect and deliver scalable, reusable AI services across CX, Monetization and Productivity that can be rapidly adopted and adapted across VSA business domains, reducing time-to-value and maximising impact.
• Real-world ML products: develop machine learning and recommender products that solve real business problems, taking account of user needs, the technology landscape and operational constraints.
• Governance and lifecycle: establish and maintain a unified AI services repository with robust governance, operational frameworks and lifecycle management to ensure compliance, consistency and efficiency.
• Efficiency at scale: drive tangible efficiency gains through scaled deployment of classical ML, GenAI and agentic AI solutions, in line with Vodacom’s Technology framework.
• Domain coverage: champion AI best practice across key VSA domains including CVM, Customer Experience, Network, Channels, Enterprise and Supply Chain, ensuring alignment with strategic AI business cases.

Value Delivery & Commercial Impact

• Commercial targets: work closely with the VSA CVM and commercial teams to deliver against revenue, retention and cost-efficiency targets through data science and AI.
• Delivery cadence: drive delivery through the quarterly PI (Programme Increment) planning cycle, prioritising value-producing projects across the VSA portfolio.
• Data asset prioritisation: support the prioritisation of internal and external data assets and work with technology partners to set key requirements for data sourcing.
• KPIs and measurement: define and track KPIs for AI output such as adoption rates, time-to-value and model efficacy across use-case categories, providing evidence-based insight that drives strategic decisions.

Partnerships, Ecosystem & Innovation

• Hyperscaler partnerships: build and manage strategic relationships with hyperscalers (AWS, Google Cloud, Microsoft Azure, Huawei) to strengthen delivery capability, accelerate prototyping and leverage cloud-native AI tooling.
• Vodafone ecosystem: contribute to and leverage the Vodafone Group AI ecosystem, driving re-use of standardised frameworks and global best-practice sharing.
• Representation: represent Vodacom South Africa in AI forums, industry bodies and partner engagements to build thought leadership and strategic relationships.

People, Culture & Capability Building

• Team leadership: lead, inspire and develop a high-performing team of data scientists, AI engineers, MLOps practitioners and solution architects within the VSA Big Data function.
• Culture of innovation: foster a culture of experimentation and continuous learning, with a focus on responsible and ethical AI development.
• AI literacy: drive AI literacy and capability uplift across the VSA business, enabling broader adoption and embedment of AI in day-to-day operations.
• Mentorship: mentor and develop senior and emerging data scientists, establishing Big Data and ML standards for the VSA team.

The ideal candidate for this role will have:

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, Economics or a related quantitative field (essential).
• Master’s degree in a quantitative field will be advantageous.
• A relevant executive leadership or management certification (e.g. MBA or equivalent) is advantageous.
• A minimum of 10 to 15 years of progressive experience in AI, Data Science or related fields, with at least 5 years in a senior technical leadership role.
• Proven track record of designing and delivering large-scale AI products, platforms or services in a complex, commercial / consumer environment.
• Deep hands-on experience in GenAI, Large Language Models (LLMs), agentic AI and real-time AI decisioning systems.
• Well versed in Customer Value Management principles, real-time recommender systems and MLOps practice.
• Extensive experience building, managing and scaling AI / ML teams across diverse, cross-functional environments.
• Demonstrated success in driving adoption and commercialisation of AI use cases with measurable business impact (revenue uplift, cost savings, CX improvements).
• Experience working with or within hyperscaler ecosystems (AWS, Google Cloud, Microsoft Azure) at an enterprise or strategic-partnership level.
• Familiarity with AI governance, ethics and regulatory compliance frameworks (including POPIA) at scale.

Technical Expertise

• Expert-level proficiency in Python and relevant AI / ML languages; familiarity with R, Scala or Java is advantageous.
• Deep knowledge of machine learning and deep learning frameworks including PyTorch, TensorFlow, scikit-learn, H2O and XGBoost.
• Expertise in LLM architecture, fine-tuning, prompt engineering and Retrieval-Augmented Generation (RAG) patterns.
• Hands-on MLOps and LLMOps experience covering CI/CD pipelines, model versioning, monitoring and drift detection, using tools such as MLflow, Kubeflow or SageMaker.
• Strong cloud-native AI deployment experience across AWS (SageMaker, Glue, Athena, Lambda, OpenSearch), GCP and/or Azure ML.
• Proficiency in containerisation and orchestration technologies including Docker and Kubernetes.
• Experience with real-time and batch inference architectures, recommendation systems, NLP and computer vision at scale.
• Working knowledge of data engineering platforms and structured (SQL) and unstructured data tools (PySpark, NoSQL, streaming frameworks such as Kafka or Flink).
• Familiarity with advanced analytics and visualisation tools such as Tableau, Power BI, Qlik Sense, Apache Superset, Grafana or Plotly.

Leadership & Behavioural Competencies

• Exceptional technical leadership presence with the ability to influence and engage C-suite stakeholders and partners.
• Design and systems thinking in relation to AI and machine learning ecosystems at enterprise scale.
• Entrepreneurial mindset with a bias for action, pace and delivery in ambiguous, fast-changing environments.
• Outstanding communication and storytelling skills, able to present complex technical content to technical and non-technical audiences with impact.
• Ability to test hypotheses from raw datasets, draw meaningful conclusions and communicate results verbally, in writing and through effective visualisation.
• Demonstrated ability to build, motivate and retain high-performing, diverse technical teams.
• Customer-obsessed approach: passionate about leveraging AI to exceed customer expectations and create genuine user value.
• High ethical standards with a commitment to responsible AI development, fairness and transparency.

Closing date for Applications: 13 July 2026