Senior Data Scientist

About the Role

The number 1 Top Employer in South Africa. Certified by the Top Employer Institute 2026.

Responsibilities

• Create AI/IA products that provide new services to Vodacom and its stakeholders.
• Develop, validate and productionise advanced machine learning models using large and varied datasets, applying strong statistical modelling, feature engineering, model evaluation and optimisation skills in partnership with technology teams.
• Contributing to the wider community to enable AI capability across Vodafone globally.
• Development of machine learning models for various areas of the business on the Big Data Platforms.
• Track machine learning model performance and business outcomes, including campaign uplift, incremental revenue and return on investment, and communicate insights through clear reporting and compelling data visualisations.
• Work with lead and principal data scientists to deliver key strategic initiatives to meet the needs of business customers.
• Works in partnership with Big Data Engineering team to automate, integrate & productionize AI workloads.
• Partner with business decision-support and commercial teams to translate analytical findings into practical recommendations, advise on campaign targeting decisions, and identify opportunities to improve customer and revenue outcomes.
• Design and evaluate controlled experiments and A/B tests for customer campaigns, defining hypotheses, treatment and control groups, success metrics, statistical significance and post-campaign measurement.
• Mentorship to data scientists in the team.
• Present results to technical and non- technical audiences.
• Bachelor’s or Master’s Degree in quantitative fields like Mathematics, Statistics, Economics, Computer Science Engineering, Artificial Intelligence or related fields (essential).
• A minimum of 4-6 years relevant experience in Big Data & Data Science.
• Experiencing working with and mentoring/coaching data scientists in training.
• Experience in GenAI and Large Language Models (LLMs) is a plus.
• Hands-on experience in building and optimizing recommendation systems.
• Strong hands-on experience building and operating data science and machine learning solutions on AWS, including SageMaker, Glue, Athena, Lambda, S3 and OpenSearch, with practical knowledge of scalable model training, deployment and monitoring.
• Strong data engineering and manipulation skills using SQL and PySpark, including developing, optimising and troubleshooting distributed Spark pipelines for large structured and unstructured datasets.
• Proficiency in at least one relevant programming language: Python, R, Java.
• Experience across major machine learning model frameworks (e.g. H2O, scikit-learn, PyTorch, Tensorflow) and techniques (e.g. random forest, gradient boosting, k-means segmentation, multiple regression, factor analysis, time-series forecasting).
• Knowledge of MLOps and LLMOps concepts and deployment of models through batch and real-time architectures.
• 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.
• Real-time Decisioning & Intelligence use case deployment and evaluation experience.
• 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