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Data Scientist

Vodafone Global Enterprise Gauteng about 10 hours ago
Full-time
Information Technology

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.