Academic and Professional Qualifications and Knowledge
Bachelor's Degree in a quantitative or technical field such as Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Statistics, Information Systems, or a related discipline.
Master's Degree in a quantitative or technical field such as Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Statistics, Information Systems, or a related discipline.
PhD in Artificial Intelligence, Machine Learning, Data Science, Intelligent Automation or a related discipline is added advantage.
Years and Nature of Experience
Minimum of ten (10) years' experience in Artificial Intelligence, Machine Learning, Data Science and Intelligent Automation or related disciplines.
At least five (5) years' experience leading the design, development, deployment, and operationalization of enterprise Artificial Intelligence, Analytics, or Intelligent Automation solutions.
Minimum of three (3) years' experience managing and developing multi-disciplinary technical teams comprising Artificial Intelligence, Machine Learning, Automation, Data Science, and Data platform professionals.
Proven experience working within Data & Analytics, Artificial Intelligence, Business Intelligence or Intelligent Automation functions, delivering classic AI, Generative AI, and Intelligent Automation solutions within a highly regulated environment such as central banking, financial services, government, telecommunications or regulatory institutions.
Demonstrated expertise in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, AI Agents, and Retrieval-Augmented Generation (RAG).
Proven experience implementing Intelligent Automation solutions using Robotic Process Automation (RPA), workflow automation, business process orchestration, and low-code automation platforms such as Power Automate, UiPath, Automation Anywhere, Blue Prism, or equivalent technologies.
Hands-on experience deploying AI solutions into production environments and managing the full AI lifecycle, including model development, testing, deployment, monitoring, retraining, and performance optimisation.
Experience designing enterprise AI and automation architectures, including integration with business applications, APIs, enterprise data platforms, and cloud environments.
Good knowledge of cloud-based AI platforms such as Azure AI, Azure Machine Learning, Azure OpenAI, Databricks, AWS AI/ML, Google AI, or equivalent enterprise platforms.
Experience implementing controls for AI model validation, monitoring, explainability, security, privacy, and compliance.
Familiarity with international standards and frameworks such as ISO 42001, ISO 27001, NIST AI Risk Management Framework, EU AI Act, or equivalent governance frameworks.
Technical and Professional Competencies
Strong expertise in Artificial Intelligence (AI), Machine Learning (ML), Generative AI, Intelligent Automation, and enterprise AI platforms.
Proven experience in AI/ML strategy formulation, execution, and operationalisation of AI and automation solutions at enterprise scale.
Demonstrated capability in RPA, workflow automation, MLOps, AI governance, model risk management, and AI solution architecture.
Strong analytical, problem-solving, and innovation skills, with the ability to translate business challenges into technology-enabled solutions.
Leadership and Management Competencies
Strategic leadership with the ability to align AI and automation initiatives to organisational objectives.
Proven experience leading, developing, and motivating high-performing multidisciplinary technical teams.
Strong programme, project, vendor, budgeting, and resource management skills.
Demonstrated ability to drive innovation, change, execution excellence, and value realisation across complex transformation initiatives.
Strong change management capability, including driving adoption of AI and automation technologies.
Behavioural Competencies
Excellent stakeholder engagement, influencing, and relationship management skills.
Strong communication and presentation skills, with the ability to convey complex technical concepts to both technical and non-technical audiences.
Results-oriented, adaptable, and committed to continuous learning, innovation, and improvement.
High levels of professionalism, accountability, and sound judgement in managing emerging technologies and associated risks.
GK
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