Data Scientist at Vodafone Global Enterprise

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:

• 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 evaluation experience.
• Ability to work independently and collaboratively in a fast-paced, agile environment.
• Curious, adaptable, and continuously learning in a rapidly evolving AI landscape.

Core competencies, knowledge, and experience:

Core (Mandatory)

Strong hands-on experience with:

• LLMs (e.g., OpenAI, Claude, Gemini)
• RAG architectures and vector databases
• Prompt engineering and evaluation frameworks

Experience designing and building:

• Agentic AI systems or AI-driven workflows
• Tool/API orchestration within LLM applications

Strong understanding of:

• Hallucination mitigation and grounding techniques
• Responsible AI and safety guardrails
• LLM evaluation and observability

Engineering & Deployment

Experience with:

• Python (preferred) and API frameworks (FastAPI/Flask)
• Cloud platforms (AWS/GCP/Azure)

Understanding of:

• LLMOps / AI system lifecycle
• Real-time and batch processing architectures

Data Science Foundations

Experience with:

• Machine learning algorithms (classification, regression, clustering)
• NLP techniques (traditional and modern)
• Strong data manipulation skills (SQL, PySpark, etc.)

Preferred (Differentiators)

Experience with:

• Multi-agent frameworks (LangGraph, AutoGen, CrewAI, etc.)
• Conversational AI and chatbot platforms
• Speech and voice analytics
• CX or telecom use cases
• Experience building end-to-end AI systems, not just models

We make an impact by offering:

• Enticing incentive programs and competitive benefit packages
• Retirement funds, risk benefits, and medical aid benefits
• Cell phone and data benefits, advantages fibre connection discounts, and exclusive staff discounts offered in collaboration with partner companies

Closing date for Applications: 27 August 2026.