Senior Artificial Intelligence and Machine Learning Specialist

The Senior AI and ML Specialist is accountable for leading Postbank’s enterprise AI and machine-learning capability for assigned domains. The role defines AI/ML strategy, standards, governance, responsible-AI controls and MLOps practices, prioritises the AI/ML portfolio, directs the AI and ML Developer, and provides authoritative specialist leadership over high-impact AI/ML solutions that support secure, ethical, auditable and scalable operational decision-making.

• Translate Postbank priorities into an AI/ML roadmap, standards and delivery portfolio for assigned domains.
• Prioritise AI/ML initiatives based on strategic value, feasibility, risk, data readiness, regulatory implications, resource availability and operational benefit.
• Define standards for responsible AI, solution design, model development, validation, explainability, deployment, monitoring, security and retirement.
• Advise the Head:
  Analytics and senior stakeholders on AI opportunities, constraints, risks, investment needs and implementation options
• Evaluate new AI technologies, tools, vendors and platforms and recommend adoption, containment or rejection based on value and risk.

• Lead complex AI/ML, deep-learning, NLP, optimisation, automation or generative-AI initiatives from concept to deployment handover.
• Approve or challenge AI architecture, algorithm choices, MLOps design, testing strategies, monitoring thresholds and integration approaches.
• Coordinate implementation dependencies with technology, BI, automation, data, risk, operations, compliance and business stakeholders.
• Oversee design and maintenance of MLOps practices for secure, scalable, repeatable and auditable AI/ML delivery.
• Present AI/ML findings, solution options, benefits, limitations and risk implications to executive, operational and technical audiences.

• Own AI/ML governance artefacts, model registers, responsible-AI evidence, deployment documentation and monitoring evidence for assigned domains.
• Ensure compliance with POPIA, FSCA requirements, internal data-governance policies, information-security standards and model-risk controls.
• Oversee fairness, bias, explainability, privacy, robustness, security, drift and performance monitoring for AI/ML solutions
• Coordinate audit, assurance, regulatory or internal-control evidence relating to AI/ML solutions.
• Escalate material ethical, operational, security or compliance risks and recommend control improvements.

• Lead, allocate and monitor work of AI and ML Developer resources in line with portfolio priorities, quality gates and deadlines.
• Set role expectations, review performance inputs, coach AI engineering capability and identify development needs
• Contribute to recruitment, onboarding, probation input, workforce planning and succession planning for AI/ML roles.
• Manage workload, continuity, leave planning and delivery risk across AI/ML work streams
• Promote a professional, responsible, secure and innovation-oriented AI delivery culture aligned to Postbank values

• Bachelor’s degree in Mathematics, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Statistics, Applied Mathematics, or a related quantitative/technology field (NQF Level
  7).
• Honours or Masters degree in AI, machine learning, data science, computer science, analytics or related field (NQF Level 8/9) (Ideal)
• 8+ years Relevant Artificial Intelligence and Machine Learning-related experience at a Specialist level
• 5+ years Managerial / Team Lead experience
• Relevant experience in the Banking Industry (Advantageous)

A phased skills pathway for strengthening data engineering, business intelligence, predictive AI, automation, optimisation and strategic analytics capability.

• Data Pipeline Modernization: Database optimization, automated ETL pipelines and stored procedures.
• Advanced Business Intelligence: Advanced data modeling, context filtering, row-level security and cloud deployment.
• Enterprise Analytics Legacy Integration: Statistical profiling, macro migration and legacy predictive validation.

• Behavioral Modeling & Marketing AI: Binary classification and feature engineering for upsell/cross-sell propensity modeling.
• Lead Automation & Income Estimation: Regression trees, ensemble…