Senior Data Scientist (Graph Analytics & AI) – 12-Month Contract

A leading bank in Sandton is seeking a highly skilled Senior Data Scientist to join its advanced analytics and data science team. This role is ideal for an experienced professional with a strong background in machine learning, graph analytics, AI/GenAI solutions, and cloud-based data platforms, who is passionate about solving complex business challenges through data-driven innovation.

The successful candidate will play a key role in developing predictive models and advanced analytical solutions to support critical banking initiatives, including fraud detection, financial crime prevention, risk intelligence, customer analytics, and AI-enabled decision-making.

• →Design, develop, and deploy advanced machine learning and predictive analytics models.
• →Apply graph analytics techniques to uncover patterns, relationships, and hidden insights within complex data ecosystems.
• →Develop and maintain knowledge graphs to support AI and Generative AI use cases.
• →Perform advanced feature engineering to enhance model performance and accuracy.
• →Build scalable data science solutions using cloud-native technologies and modern data platforms.
• →Collaborate with business stakeholders, data engineers, architects, and technology teams to deliver high-impact analytical solutions.
• →Evaluate, optimise, monitor, and improve model performance throughout the model lifecycle.
• →Support fraud detection, anti-money laundering (AML), financial crime, customer intelligence, and risk analytics initiatives.
• →Drive innovation through the adoption of emerging AI, machine learning, and graph technologies.
• →Ensure compliance with data governance, model risk management, and banking regulatory requirements.

• Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.
• 7+ years of experience in Data Science, Advanced Analytics, or Machine Learning roles.
• Strong proficiency in Python and related data science libraries.
• Proven experience developing and deploying machine learning models in enterprise environments.
• Hands-on experience with Graph Analytics, Graph Databases, or Knowledge Graph technologies.
• Strong understanding of supervised and unsupervised machine learning techniques.
• Experience with AI and Generative AI solutions and their practical application within large organisations.
• Experience working with cloud-based platforms and modern data architectures.
• Strong SQL and data manipulation skills.
• Experience working with large-scale datasets and distributed data environments.
• Excellent analytical, problem-solving, and stakeholder engagement skills.

• Banking, Financial Services, Insurance, or FinTech experience.
• Experience in Fraud Detection, Financial Crime, AML, Risk Analytics, or Customer Intelligence.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with MLOps, model deployment, and production monitoring.
• Knowledge of graph technologies such as Neo4j, TigerGraph, Amazon Neptune, or similar platforms.
• Experience working within Agile delivery environments.

• Strong commercial and business acumen.
• Ability to translate complex analytical findings into actionable business insights.
• A collaborative team player who can work across business and technology teams.
• Passion for innovation, AI, and solving complex banking challenges through data.
• Ability to work independently and manage multiple priorities in a fast-paced environment.