Roles and Responsibilities
Strategy & Leadership
Lead the definition, development, and execution of the enterprise Data strategy, incorporating analytics and AI, ensuring alignment with CGIC's business objectives and regulatory expectations.
Provide strategic guidance and roadmaps for data investments and initiatives, focusing on building scalable analytics/AI delivery.
Collaborate with senior leadership, EXCO/Board, and stakeholders to translate business requirements into effective data solutions, emphasizing value framing and measurable outcomes.
Drive a culture of data-driven innovation, governance, and continuous improvement across the organization.
Portfolio & Architecture Governance
Develop, implement, and maintain the Data portfolio strategy, including prioritized use-case portfolio delivering measurable value.
Monitor data portfolio alignment to business strategy, ensuring consistency, data quality, ownership, access, and lineage in collaboration with IT and business units.
Establish AI governance framework (risk, controls, model lifecycle) aligned to insurance regulatory expectations.
Identify, manage, and resolve architecture deviations across the data lifecycle, aligning data platform and integration with IT (without direct ownership).
Technology Evaluation & Adoption
Lead the identification, research, and evaluation of new data, analytics, and AI technologies, with a focus on cloud data platforms.
Track and measure adoption rates, time-to-adopt, and impact of new data capabilities, ensuring they support insurance-specific needs like risk assessment and claims analytics.
Ensure proactive scanning of industry trends, particularly in financial services/insurance, to leverage opportunities that enhance business objectives.
Performance, Value & ROI Measurement
Track and measure Data portfolio ROI, financial benefits, and overall value delivery, with emphasis on first 6 - 12 months outcomes.
Key Outcomes for 6-12 months
Data & AI strategy and operating model agreed and in execution
Prioritised use-case portfolio delivering measurable value
Data governance foundation (quality, ownership, access, lineage) in place in collaboration with IT and business
AI governance framework (risk, controls, model lifecycle) aligned to regulatory expectations
Team hired and operating (data engineering; data analytics / data science)
Monitor time-to-market for new data initiatives and performance against delivery expectations.
Provide regular updates and reports on initiatives, performance metrics, and portfolio progress to EXCO/Board/Group.
Security, Compliance & Risk Management
Ensure data solutions adhere to security standards, regulatory requirements (e.g., data privacy, model risk in insurance), and industry best practices.
Partner with risk/control teams to proactively identify, mitigate, and resolve data-related risks and vulnerabilities, with comfort in a risk/control environment.
Develop and maintain strategies for data protection, disaster recovery, and business continuity, including governance policies, standards, controls, and documentation.
Stakeholder Engagement & Communication
Serve as a strategic liaison between business leaders, IT teams, and stakeholders to ensure alignment and effective communication.
Clearly articulate the value and benefits of data initiatives across the organisation, with strong business translation skills.
Influence peers and operate under ambiguity, writing clearly to drive consensus.
Team Leadership & Development
Lead, mentor, and coach data teams (engineering, analytics/science), hiring and developing talent to build a high-performing function.
Manage cross-functional teams in the delivery of the portfolio, ensuring alignment with business imperatives, and partner with vendors where needed.
Promote professional development, knowledge sharing, and certification within the team.
Measure and drive employee engagement, satisfaction, productivity, and capability growth.
Qualifications & Experience
Bachelor's degree in Computer Science, Information Systems, Data Science/Analytics, Engineering, or a related field.
Postgraduate qualification and/or a Master's degree in a related field or MBA will be advantageous.
10+ years' experience in data roles, with in-depth project management experience. Minimum 5 years leading data/analytics teams (delivery + stakeholders).
Experience implementing governance (not just dashboards), including data quality, ownership, access, lineage, and AI/ML lifecycle.
Strong business translation skills and comfort with risk/control environments.
Insurance/financial services exposure is highly advantageous.
Hands-on experience with enterprise applications and tools relevant to insurance (e.g., data platforms for risk modelling, claims data).
Experience with data modelling, ETL pipeline development, and data governance frameworks.