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.

Key Responsibilities

• 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.

Required Skills & Experience

• 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.

Preferred Experience

• 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.

What We're Looking For

• 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.

Why Join?

This is an opportunity to work on cutting-edge AI, Machine Learning, Graph Analytics, and Financial Crime solutions within one of South Africa's leading banking environments. You will contribute to strategic initiatives that directly impact customer experience, risk management, and enterprise decision-making while working alongside highly skilled data and technology professionals.

Interested? Apply now with your updated CV and availability.