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Head: Data & AI

Job in Johannesburg, 2000, South Africa
Listing for: Old Mutual South Africa
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Security, Data Analyst, Data Science Manager
Job Description & How to Apply Below

Let’s Write Africa’s Story Together!

Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.

Job Description

Lead the Data function at Credit Guarantee Insurance Corporation (CGIC) to build and drive data strategy, governance, and scalable analytics/AI delivery that enables business value, supports risk management, and aligns with regulatory requirements in the insurance sector. This role is pivotal in establishing foundational data capabilities, prioritizing value-driven use cases, and fostering a data-driven culture to enhance operational efficiency, decision‑making, and competitive advantage in trade credit insurance.

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
  • Prioritized 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…
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