Data Scientist

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Vodacom is a leading African mobile communications company, serving over 200 million customers across South Africa, Tanzania, DRC, Mozambique, Kenya, Lesotho, Egypt, and Ethiopia. Our mobile networks reach a population of approximately 250 million people. Through Vodacom Business Africa (VBA), we also deliver managed services to enterprises in over 40 countries across the continent.

We are truly data-driven, committed to delivering intelligent solutions that enhance customer experience and business performance. Our Big Data and AI team plays a pivotal role in enabling this transformation by supporting the CX and Digital space with scalable, innovative data capabilities.

Role Purpose/Business Unit:

We are looking for a Data Scientist specializing in Generative AI and Agentic AI systems to design and deliver next-generation, AI-powered customer experience solutions.

This role is focused on building production-grade LLM-powered systems and agentic workflows that enable:

• Real-time decisioning
• Intelligent automation
• Proactive and personalized customer engagement

You will operate at the intersection of LLMs, agent orchestration, and customer intelligence, delivering scalable solutions across Vodacom’s digital channels, customer care platforms, and markets.

This role operates across text, voice, and multimodal customer data, transforming raw customer interactions into intelligent, AI-driven actions at scale.

Your responsibilities will include:

GenAI & LLM System Development (Primary Focus)

• Design, build, and deploy LLM-powered applications including:
  • Retrieval-Augmented Generation (RAG)
  • Conversational AI
  • Summarisation, classification, and recommendation systems
• Develop RAG architectures integrating structured and unstructured enterprise data
• Implement robust prompt engineering, evaluation frameworks, and guardrails
• Build LLMOps pipelines covering orchestration, monitoring, evaluation, and optimisation
• Ensure solutions are scalable, secure, and production-ready

Agentic AI & Workflow Automation (Core Capability)

• Design and implement agentic AI systems capable of:
  • Multi-step reasoning and planning
  • Tool and API orchestration
  • Autonomous execution with feedback loops
• Develop multi-agent workflows to support:
  • Customer query resolution
  • CX insights generation
  • End-to-end journey orchestration
• Implement human-in-the-loop mechanisms, approvals, and safety controls
• Integrate AI agents into:
  • Chatbots and virtual assistants
  • IVR and voice systems
  • Backend operational workflows
  • Relevant application workflows

Customer Experience (CX) Intelligence (High Impact)

• Design and build scalable AI solutions to extract value from complex unstructured customer data, including:

  • Call centre audio recordings and voice data
  • Speech-to-text transcripts and conversational logs
  • Chatbot and digital interaction data
  • NPS and survey verbatims (free-text feedback)
  • Customer emails, service requests, and support tickets

• Develop end-to-end pipelines that transform raw unstructured data into actionable intelligence using:

  • LLMs and Generative AI
  • NLP and speech/voice analytics
  • Multilingual processing techniques

• Build models and LLM-driven systems to enable:

  • Sentiment, emotion, and behavioural signal detection (text + voice)
  • Customer intent classification and journey mapping
  • Root cause analysis and large-scale theme extraction
  • Call summarisation, tagging, and quality evaluation
  • Identification of churn signals, friction points, and experience drivers

• Deliver real-time and near real-time CX intelligence, enabling:

  • Dynamic next-best-action recommendations
  • Proactive issue detection and resolution
  • Personalised customer engagement across channels

• Translate insights into automated CX actions through agentic systems, including:

  • AI agents triggering workflows based on detected customer issues
  • Intelligent routing and resolution of queries

  Closed-loop systems connecting insight action+ outcome tracking

Data Science & Traditional AI

• Develop predictive models where required, including:
  • Propensity based prediction models
  • Segmentation and Proactive Calling Models
• Perform data analysis, feature engineering, and statistical modelling
• Work with structured and unstructured datasets to support GenAI use cases

Engineering & Productionisation

• Build scalable pipelines integrating:
  • Data ingestion and processing
  • Vector databases and retrieval systems
  • APIs and orchestration layers
• Deploy solutions using cloud-native technologies (e.g. AWS/GCP/Azure)
• Work closely with technology teams to productionise AI solutions using:
  • Microservices and APIs
  • Containerisation (Docker/Kubernetes)

Leadership & Collaboration

• Champion GenAI and Agentic AI initiatives across CX and Digital teams
• Mentor and uplift data scientists in emerging AI capabilities
• Translate complex AI outputs into clear, business-aligned value
• Collaborate with cross-functional teams including Group Technology, Product, CX stakeholders across Vodacom Group The ideal candidate for this role will have:

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• Bachelor’s Degree in quantitative fields like Mathematics, Statistics, Computer Science, Engineering, Artificial Intelligence or related fields (essential). Master’s degree is advantageous.

• A minimum of 3-5 years relevant experience in Big Data, Data Science, AI/ML, or Engineering roles, with demonstrated delivery of end-to-end AI solutions in productions environments.

• Experiencing working with and mentoring/coaching data scientists in training.

• Experience with GenAI, LLMs, and MLOps/LLMOps frameworks.

• Experience in data manipulation: use of structured data tools (e.g., SQL), and unstructured data platforms (e.g. PySpark, NoSQL).

• Strong hands-on experience building and deploying Core Generative AI and Agentic AI applications.

• Proficiency in at least one relevant programming language: Python (preferred).

• Experience across major machine learning model frameworks (e.g. H2O, scikit-learn, PyTorch, Tensorflow) and traditional techniques (e.g. random forest, gradient boosting, k-means segmentation, multiple regression).

• Hands-on experience with cloud-native AI/ML deployment, preferably on AWS.

• Exposure to cloud native deployment of models and working with containerized technologies such as Docker and Kurbernetes.

• Strong experience working with structured and unstructured data.

• Knowledge of MLOps and LLMOps concepts and deployment of models through batch and real-time architectures.

• Experience with APIs and application frameworks (e.g. FastAPI, Flask).

• Familiarity with modern AI/ML and data tooling ecosystems.

• Ability to translate business problems (especially in Customer Experience) into scalable AI solutions.

• Professional and/or academic experience in Big Data analytics & deployment of models and algorithms to solve real-world problems (with deep statistical and machine learning modelling expertise).

• Familiarity with visualization tools (e.g. Tableau, Qlik, D3, Apache Superset, Plotly, PowerBI, Opensearch, Grafana).

• Good interpersonal communication and presentation skills.

• Ability to work in a fast-paced environment.

• Analytical and expansive thinking with a strong desire to deliver and develop.

• Experience working with teams and coaching data scientists.

• Strong communication and presentation skills.

• Design & Systems Thinking in relation to AI and Machine Learning Eco Systems.

• Real-time Decisioning & Intelligence use case deployment and evalu