Head of Artificial Intelligence at Co-operative Bank of Kenya

The Role

The successful jobholder will be expected to:

• Drive AI Strategy: Develop and execute the Bank’s multi-year AI strategy and roadmap, aligned with corporate objectives and emerging technology opportunities.
• Accelerate AI Innovation: Identify, prioritize and deliver high-impact AI use cases across credit, fraud management, collections, customer service, technology and other business areas.
• Lead AI Delivery: Oversee cross-functional AI teams from ideation and experimentation through deployment, adoption and benefits realization.
• Establish AI Standards: Define enterprise AI architecture, engineering standards and lifecycle practices, including MLOps, production monitoring, reusable AI services and cost optimization.
• Champion Responsible AI: Establish and maintain robust AI governance frameworks that promote security, fairness, transparency, accountability and regulatory compliance throughout the AI lifecycle.
• Enable Business Transformation: Partner with business leaders to embed AI into business processes, drive adoption and change management, and track performance against agreed business outcomes.
• Strengthen Data Foundations: Collaborate with Data & Analytics teams to ensure AI solutions are supported by trusted, governed and reusable data.
• Build AI Capabilities: Lead the development of a high-performing AI team and AI Centre of Excellence, attract and nurture specialist talent, and champion AI literacy across the Bank.

Qualifications, Skills & Attributes

The successful jobholder will be required to possess the following qualifications:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering, Mathematics, Information Technology or a related field.
• Master’s degree in Artificial Intelligence, Data Science, Computer Science, Business Administration (MBA), Analytics or a related discipline.
• Professional certifications in AI, Machine Learning, Cloud Platforms, Data Science or Enterprise Architecture will be an added advantage.
• At least 10 years’ experience in technology, data, analytics, digital transformation or AI-related disciplines.
• At least 5–7 years in senior leadership, overseeing enterprise-scale AI, analytics or technology functions.
• Proven track record in delivering large-scale AI and Machine Learning programmes, from strategy and design to production deployment and measurable business impact.
• Demonstrated experience leading multidisciplinary teams comprising data scientists, engineers, architects and business stakeholders.
• Experience in banking, financial services, fintech, telecommunications or other highly regulated industries.