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The project focuses on supporting complex data, process, and AI transformation programmes within legal or regulatory environments (e.g. EFSA context). The role involves designing and delivering AI-enabled solutions that enhance decision-making, automate processes, and improve efficiency while ensuring compliance with legal, regulatory, and governance frameworks. The position acts as a bridge between business, legal, data, and technology stakeholders, translating business and legal requirements into scalable AI-driven solutions.
Microsoft Azure AI Services (Azure OpenAI, Cognitive Services)
Machine Learning frameworks (conceptual or hands-on exposure)
Data platforms (Azure Data Lake, Synapse, Databricks – nice to have)
Search & retrieval technologies (vector search, RAG architectures)
Azure DevOps / Jira (Agile delivery and backlog management)
Power BI / Excel (data analysis and reporting)
M365 tools (Teams, SharePoint, PowerPoint)
Optional: Python / SQL
Experience in:
AI-enabled transformation programmes (including GenAI / Machine Learning)
Working in or with legal, regulatory, or compliance-driven environments
Redesigning end-to-end business processes leveraging AI
Eliciting and documenting AI-related requirements and use cases
Delivering AI components into production environments
Integrating AI services within enterprise ecosystems (e.g. Azure-hosted AI, data platforms, vector search)
Conducting data analysis with strong attention to data quality and governance
Modelling complex decision processes combining human and AI inputs
Solid understanding of AI/ML concepts and decision intelligence frameworks
Ability to align AI solutions with legal and regulatory requirements
Strong expertise in process optimisation and intelligent automation
Proven ability to translate business and legal needs into technical solutions
Excellent stakeholder management in complex, multi-stakeholder environments
Strong analytical and problem-solving mindset
Experienced in using AI tools in day-to-day workflow
Experience with data platforms such as Azure Data Lake, Synapse, Databricks
Knowledge of Python or SQL
Drive AI-enabled transformation initiatives in complex, regulated environments
Elicit, analyse, and document AI use cases, requirements, and business needs (including legal and compliance aspects)
Lead end-to-end process redesign with integrated AI capabilities
Design and support implementation of decision intelligence models combining human judgment and AI outputs
Contribute to delivery and deployment of AI components into production environments
Ensure integration of AI services within enterprise architectures (Azure AI, data platforms, vector search)
Perform data-driven analysis with focus on data quality, traceability, and compliance
Collaborate with multi-disciplinary stakeholders (legal, business, IT, data, external providers)
Ensure compliance with governance, security, legal, and enterprise architecture standards
Support business analysis activities within broader transformation initiatives
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