Company Description

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.

Job Description

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.

Qualifications

Type of Qualification: First Degree
Field of Study: 

Computer Science, Statistics, Applied Mathematics, or relatedAdvanced 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 LearningProven track record of deploying ML models into production (Azure ML, AWS Sagemaker, or Databricks)Strong expertise in Python (Pandas, Scikit-learn, TensorFlow, PyTorch) and SQLSolid understanding of statistics, time series analysis, NLP, and deep learningExperience with MLOps, CI/CD pipelines, and model monitoringExposure to big data ecosystems (Spark, Databricks, Hadoop) is advantageousExperience working in financial services or large-scale enterprise environments (preferred)

Additional Information

Behavioural Competencies:

Adopting Practical ApproachesArticulating InformationChallenging IdeasConvincing PeopleEmbracing ChangeEmpowering IndividualsMaking DecisionsProducing OutputPursuing GoalsResolving ConflictShowing ComposureUpholding Standards

Technical Competencies:

Machine Learning & Deep Learning (Supervised, Unsupervised, NLP, GenAI)Statistical Modelling & Advanced AnalyticsData Wrangling & Feature EngineeringMLOps & Model Lifecycle ManagementBig Data & Distributed Systems (Spark, Databricks)Cloud ML Services (Azure ML, AWS Sagemaker)Data Governance & Model ExplainabilityBusiness Problem-Solving & Value Creation