The Head of IT for Analytics and AI is a strategic leadership role responsible for driving the organizations data-driven transformation. This position oversees the development and execution of enterprise-wide analytics and AI strategies, ensuring alignment with business goals, operational efficiency, and innovation.
The role combines deep technical expertise with visionary leadership to harness emerging technologies and deliver actionable insights.
Responsibilities:
The Employee will:
- Define and lead the analytics and AI vision, strategy, and roadmap across the enterprise.
- Align data and AI initiatives with business objectives, digital transformation goals, and IT architecture.
Data & AI Governance
- Establish governance frameworks for data quality, privacy, and ethical AI use.
- Ensure compliance with internal policies such as the CPL Artificial Intelligence Policy.
Technology Enablement
- Champion the adoption of modern platforms including SaaS, IaaS, PaaS, APIs, microservices, and event-driven IT.
- Lead the evaluation and deployment of generative AI and predictive analytics tools.
Operational Excellence
- Oversee the integration of analytics into IT operations, including infrastructure, service management, and enterprise applications.
- Drive continuous improvement through data-driven insights and process optimization.
Team & Stakeholder Management
- Build and lead cross-functional teams of data scientists, engineers, and analysts.
- Collaborate with business units, HR, finance, and compliance to embed analytics into decision-making.
Preferred Qualifications, Capabilities, and Skills:
- Bachelors or Masters degree in Computer Science, Data Science, Information Systems, or related field.
- 10+ years of experience in IT leadership roles, with at least 5 years in analytics and/or AI.
- Proven track record of delivering enterprise-scale analytics and AI solutions.
- Excellent team player, ability to work well within teams and across departments.
- Ability to handle high-pressure situations and navigate complex environments.
- Experience of championing organizational evolution, e.g. leading initiatives, products, services, or interactions.
Skills Required:
- Deep understanding of business models, financial analysis, and risk management.
- Expertise in agile and lean methodologies, ITIL, and enterprise architecture frameworks.
- Familiarity with AI lifecycle management, including model development, deployment, and monitoring.
- Strong grasp of emerging technologies such as generative AI, automation, and data mesh.
- Knowledge of business models, operating mod