Senior Tech, Data & AI Auditor
Listed on 2026-10-19
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IT/Tech
AI Engineer (Applied/Software), IT Business Analyst, Information Security & Data Protection, Data Analyst
The position is based either in London, Paris or Zurich (depending on the successful candidate's location). The successful candidate will support the global GIA team based in the EMEA, UK, US and APAC regions. This is a unique and important role within GIA. The successful candidate will bring strong expertise in technology, data, AI development, testing, governance and risk management, helping GIA provide effective assurance over the organisation's expanding use of digital technologies and AI-enabled solutions.
The role has a dual focus: (1) supporting audits over technology, data, automation and AI-related risks, applications, processes and controls; and (2) helping to shape the future of GIA by developing and applying data analytics, automation solutions, and AI tools that enhance audit effectiveness, efficiency and insight generation.
This role is a strong accelerator to leverage and expand your expertise, tackle real business challenges, and deliver tangible impact. The successful candidate will work closely with both GIA teams and SCOR's wider Technology & Data communities, acting as a bridge between technical innovation and risk-based assurance.
Candidates may come from a variety of technology, data, AI or analytical backgrounds and, whilst internal audit or enterprise risk management experience would be advantageous, it is not essential. The successful candidate will be supported by experienced members of the GIA team, providing an opportunity to develop audit and assurance expertise alongside their existing technical skills. We are seeking curious, motivated individuals who are keen to apply their technology, data and AI skills in a new and evolving context while helping to transform the future of GIA.
ResponsibilitiesThis description takes into account the principal responsibilities and is not to be considered exhaustive:
Technology, Data & AI Assurance- Support audits covering technology platforms, cloud environments, data management, automation initiatives, AI solutions and emerging technologies.
- Evaluate technology development, change management, model governance, AI lifecycle management, data quality and cybersecurity controls.
- Review AI solutions, machine learning models and intelligent agents for governance, accountability, explainability, fairness, transparency and regulatory compliance.
- Perform risk assessments and identify emerging technology and AI risks that should be incorporated into audit planning.
- Support auditors in evaluating complex technology-related control environments and translating technical concepts into business risks and audit conclusions.
- Contribute to the assessment of the design and effectiveness of governance, risk management frameworks, internal controls and oversight arrangements for technology and AI-related activities.
- Design and execute advanced data analytics to identify risks, anomalies, trends and control weaknesses.
- Develop automated testing and continuous auditing capabilities.
- Create dashboards, visualisations and data-driven insights to support audit planning, fieldwork and reporting.
- Promote the use of analytics across the audit lifecycle and build data literacy within the audit team.
- Identify opportunities to automate audit activities and improve audit productivity.
- Design, build and deploy AI-enabled tools, workflow automations and intelligent agents to support audit execution.
- Contribute to the development of the Internal Audit technology and innovation roadmap.
- Partner with Technology, Data & AI teams to understand significant programmes, architectures, risks and control environments.
- Act as a subject matter expert for technology, data and AI matters across the Internal Audit team.
- Provide coaching and technical guidance to auditors in technology and AI-related areas.
- Support discussions with senior management, risk functions and governance committees regarding technology and AI risk management practices.
- Maintain awareness of relevant industry developments, regulatory expectations and emerging risks.
Candidates should possess several of the following:
- 3-5+ years' experience in AI development, data engineering, data science, technology consulting, software engineering, automation, technology risk, IT audit or digital transformation.
- Practical experience designing, building, deploying, testing or reviewing technology,…
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