Senior Data Scientist

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

We are seeking an experienced Senior Data Scientist to lead the design, development, and deployment of advanced analytical and machine learning solutions. The ideal candidate will be responsible for solving complex business problems through data-driven insights, predictive modelling, and AI solutions.

This role requires strong expertise in statistical modelling, machine learning, and deep learning, along with proven experience deploying models into production within hybrid cloud environments (Azure and AWS). The Senior Data Scientist will collaborate with stakeholders across business and technology teams, ensuring solutions are scalable, explainable, and deliver measurable value.

Type of Qualification: First Degree

Field of Study: 

• Computer Science, Statistics, Applied Mathematics, or related
• Advanced degree (MSc/PhD) preferred.
• Certifications in Azure Machine Learning, AWS Sagemaker, or related platforms advantageous

Experience Required

5-8 years

• Minimum 5–8 years’ experience in Data Science and Machine Learning
• Proven track record of deploying ML models into production (Azure ML, AWS Sagemaker, or Databricks)
• Strong expertise in Python (Pandas, Scikit-learn, TensorFlow, PyTorch) and SQL
• Solid understanding of statistics, time series analysis, NLP, and deep learning
• Experience with MLOps, CI/CD pipelines, and model monitoring
• Exposure to big data ecosystems (Spark, Databricks, Hadoop) is advantageous
• Experience working in financial services or large-scale enterprise environments (preferred)

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Convincing People
• Embracing Change
• Empowering Individuals
• Making Decisions
• Producing Output
• Pursuing Goals
• Resolving Conflict
• Showing Composure
• Upholding Standards

Technical Competencies:

• Machine Learning & Deep Learning (Supervised, Unsupervised, NLP, GenAI)
• Statistical Modelling & Advanced Analytics
• Data Wrangling & Feature Engineering
• MLOps & Model Lifecycle Management
• Big Data & Distributed Systems (Spark, Databricks)
• Cloud ML Services (Azure ML, AWS Sagemaker)
• Data Governance & Model Explainability
• Business Problem-Solving & Value Creation