Manager Ai and Decision Science

Empowering Africa’s tomorrow, together one story at a time.
- With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

Job Summary

The Manager, AI and Decision Science is a strategic and operational role within the Human Capital (HC) function, responsible for building and embedding advanced analytics, artificial intelligence (AI), and emerging AI into Human Capital (HC) strategies, platforms, and workflows. The role ensures that AI capabilities deliver measurable impact on Human Capital and People driven decision-making including workforce planning, talent management, efficiency and employee experience. It is both a strategic enabler and operational integrator, designed to position the HC function as future-fit, data-driven, and digitally enabled.

Job Description

Key Focus Areas- Piloting and monitoring emerging AI and Analytics technologies relevant to HC.- Strategic implementation of AI and advanced analytics and decision science in HC.- Oversight of integration of AI solutions into HC platforms in alignment with technical partners.- Cross-functional collaboration and adoption across HC COO, CoEs, HC Tech, ITO and delivery partners.- Performance measurement and continuous optimisation of AI initiatives.- Talent development, capability building, and fostering an innovation culture.- Assurance of governance, data integrity, and ethical AI practices.

Key Accountabilities

1. Innovation & Emerging Technology- Work in alignment with the AI strategist to continuously scan the external environment for emerging AI tools, platforms, and techniques relevant to HC.- Pilot and experiment with new solutions, balancing innovation with risk and governance guardrails.- Promote an internal culture of experimentation (e.g. hackathons, proof-of-concepts) within the AI / Analytics team and across HC.- Contribute thought leadership on AI in HC, positioning the organisation as a progressive, future-fit employer.

2. Strategic AI, Decision Science and Analytics Leadership- Develop and execute a 1-2 year roadmap for AI and analytics aligned to HC and enterprise digital transformation priorities.- Translate organisational goals into AI-enabled HC strategies that enhance decision-making, workforce planning, efficiency and employee experience.- Identify and prioritise high-value use cases across HC (e.g. talent acquisition, skills mapping, attrition, performance, mobility, learning) in alignment with the HC AI CoE.- Horizon-scan industry trends, generative AI, and future-of-work technologies, advising HC leadership on risks and opportunities.

3. AI and Decision Science Integration & Solution Delivery- Oversee the design, development, and integration of independent AI/ Machine Learning (ML) models into HC workflows, systems (HCIS, LMS, talent platforms), and data pipelines.- Ensure AI solutions are scalable, modular, and aligned with enterprise architecture and data governance standards.- Collaborate with HC Tech, Group Technology, and data teams to deploy reusable AI assets (APIs, models, dashboards) for sustainable adoption.- Manage/ oversee vendor relationships and external partners to evaluate and integrate third-party AI solutions where relevant.

4. Cross-Functional Collaboration & Adoption- Partner with HC CoEs, CPOs, HC COO and Technology teams to identify, scope, and deliver AI-enabled initiatives.- Act as a bridge between technical specialists (data scientists, ML engineers) and business leaders to ensure alignment and adoption.- Lead stakeholder engagement, building trust in AI solutions though workshops, demos, and clear communication of value.- Drive change management strategies to embed data-driven decision-making and digital-first mindsets across HC.

5. Performance Evaluation & Optimization- Define success metrics and performance frameworks for AI initiatives (accuracy, adoption, ROI, user experience).- Implement monitoring and feedback loops to refine models, improve outcomes, and optimise solutions.- Regularly report on impact and recommend enhancements to maximise business and workforce value.

6. Team Leadership & Capability Building- Lead, mentor, and develop AI Research Scientists, Machine Learning Engineers and Data Scientists, setting clear OKRs and performance standards.- Foster a culture of collaboration, innovation, and continuous learning within the team.- Build broader HC capability by upskilling HC professionals in AI fluency, analytics, and digital tools.- Champion a growth mindset and ensure sustainability of AI knowledge and practices across HC.

7. Governance, Risk & Ethical AI- Define and enforce best practices for data quality, privacy, fairness, and responsible AI use in HC, in alignment with Group, the HC AI strategist and the AI CoE.- Ensure compliance with regulations