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Microsoft Azure AI Services (e.g. Azure OpenAI, Cognitive Services)
Machine Learning frameworks (conceptual understanding or hands-on exposure)
Data platforms (e.g. Azure Data Lake, Databricks, Synapse – nice to have)
Search & retrieval technologies (e.g. vector search, RAG architectures)
Azure DevOps / Jira (Agile delivery and backlog management)
Power BI / Excel (data analysis and reporting)
M365 Suite (Teams, SharePoint, PowerPoint)
Optional: Python / SQL (for data analysis or prototyping)
Minimum 4 years of experience in:
AI-enabled transformation programmes (including GenAI, Machine Learning, or Decision Intelligence)
Redesigning end-to-end business processes leveraging AI
Eliciting and documenting AI-related requirements and use cases
Delivering AI solutions into production environments
Integrating AI services within enterprise ecosystems (e.g. Azure AI, data platforms)
Performing data analysis with strong focus on data quality and governance
Designing complex decision processes combining human and AI inputs
Strong understanding of AI/ML concepts and enterprise AI architectures
Expertise in decision intelligence and process optimisation
Ability to translate business problems into AI-driven solutions
Strong analytical and data-driven mindset
Excellent stakeholder management and communication skills
Experience working in complex, regulated, or multi-stakeholder environments
Experienced in using AI tools in day-to-day workflow
Support of complex data, process, and AI transformation programmes (e.g. EFSA context)
Focus on leveraging AI (including GenAI and Machine Learning) to redesign business processes, enable intelligent decision-making, and deliver scalable AI solutions
Work within enterprise environments with strong alignment to organisational goals
Act as a bridge between business stakeholders, data teams, and technical teams
Ensure successful deployment of AI solutions into production environments
Drive AI-enabled transformation initiatives across complex business domains
Elicit, analyse, and document AI use cases, requirements, and business needs
Lead end-to-end process redesign, integrating AI capabilities to enhance efficiency and decision-making
Design and support implementation of AI-driven decision models combining human and machine inputs
Contribute to delivery and deployment of AI components into production environments
Support integration of AI services within enterprise architectures, including cloud-based solutions (e.g. Azure)
Perform data-driven analysis with strong focus on data quality, integrity, and governance
Collaborate with multi-disciplinary stakeholders (business, IT, data teams, external providers)
Ensure alignment with enterprise standards, governance, and security frameworks
Provide structured business analysis support across data, process, and AI transformation initiatives
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