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.
Responsibilities
This 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.
Internal Audit Innovation & Transformation
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.
Stakeholder Engagement & Collaboration
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.
Qualifications
Required Experience
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, automation, data analytics or AI solutions.
Hands‑on experience with modern enterprise data and AI platforms, such as Databricks, Palantir Foundry, Microsoft Fabric, Azure AI, Azure OpenAI, Snowflake, Dataiku or equivalent.
Practical knowledge of Generative AI, Large Language Models, Retrieval Augmented Generation, Agentic AI, multi‑agent systems, machine learning or predictive analytics.
Experience with AI and data solution lifecycle controls, including data quality, data lineage, model testing, prompt testing, access controls, monitoring, explainability, human oversight and governance.
Strong data analytics capability, including Python, SQL, Spark, Power BI, Tableau or equivalent tools.
Ability to translate complex technical concepts into practical business risks, control implications and clear audit conclusions.
Internal Audit experience. Experience auditing technology, data analytics or AI environments.
Insurance, reinsurance or financial services experience.
Experience with AI governance, model risk management or responsible AI frameworks.
Required Technical Competencies
Strong understanding of technology architecture, data management and modern software development practices.
Working knowledge of AI, machine learning, Generative AI, Large Language Models (LLMs) and Agentic AI.
Strong data analytics capability, including experience with platforms such as Python, SQL, Power BI, Tableau, Databricks, Palantir Foundry.
Understanding of technology risks, cybersecurity principles and control frameworks.
Ability to assess and test automated controls, algorithms and AI-enabled processes.
Ability to design innovative technology solutions to improve business processes.
Required Personal Competencies
Intellectual curiosity and passion for innovation.
Strong problem-solving and analytical skills.
Self‑starter with the ability to work independently and manage multiple priorities.
Ability to translate complex technical concepts into clear business insights.
Collaborative, adaptable and delivery‑focused.
Growth mindset with a continuous learning orientation.
Education and Professional Qualifications
Bachelor's degree (or equivalent professional experience) in one or more of the following disciplines:
Computer Science, Artificial Intelligence (AI)
Data Science, Data Analytics
Mathematics, Statistics
Professional certifications may include:
Databricks Certificates (e.g. Data Engineer, Machine Learning, Generative AI Associate or Professional)
Palantir Foundry certification or equivalent platform experience
AWS Certified Machine Learning Engineer
Google Professional Machine Learning Engineer
CISA - Certified Information Systems Auditor
- Locations Level 6, London, United Kingdom, EC2N 4BQ, GB
About Us
As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying “The Art & Science of Risk,” SCOR uses its industry-recognized expertise and cutting‑edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.
Working at SCOR means engaging with some of the best minds in the industry – actuaries, data scientists, underwriters, risk modelers, engineers, and many others – as we work together to find solutions to pressing challenges facing societies.
As an international company, our common culture is defined by “The SCOR Way.” Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.
SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.
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Senior Tech, Data & AI Auditor employer: SCOR
SCOR is an exceptional employer that fosters a collaborative and inclusive work culture, where employees engage with top industry professionals to tackle significant societal challenges. With a strong commitment to employee growth, SCOR offers innovative training opportunities and encourages the integration of data science and AI in its processes, ensuring that team members are at the forefront of the reinsurance industry. Located in the UK, SCOR provides a dynamic environment that values diversity and supports individuals with disabilities, making it a truly rewarding place to build a meaningful career.
