Senior Consultant – AI Transformation & Decision Intelligence

Tech stack:

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Microsoft Azure AI Services (e.g. Azure OpenAI, Cognitive Services)

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Machine Learning frameworks (conceptual understanding or hands-on exposure)

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Data platforms (e.g. Azure Data Lake, Databricks, Synapse – nice to have)

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Search & retrieval technologies (e.g. vector search, RAG architectures)

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Azure DevOps / Jira (Agile delivery and backlog management)

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Power BI / Excel (data analysis and reporting)

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M365 Suite (Teams, SharePoint, PowerPoint)

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Optional: Python / SQL (for data analysis or prototyping)

Requirements:

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Minimum 4 years of experience in:

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AI-enabled transformation programmes (including GenAI, Machine Learning, or Decision Intelligence)

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Redesigning end-to-end business processes leveraging AI

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Eliciting and documenting AI-related requirements and use cases

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Delivering AI solutions into production environments

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Integrating AI services within enterprise ecosystems (e.g. Azure AI, data platforms)

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Performing data analysis with strong focus on data quality and governance

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Designing complex decision processes combining human and AI inputs

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Strong understanding of AI/ML concepts and enterprise AI architectures

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Expertise in decision intelligence and process optimisation

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Ability to translate business problems into AI-driven solutions

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Strong analytical and data-driven mindset

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Excellent stakeholder management and communication skills

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Experience working in complex, regulated, or multi-stakeholder environments

Nice to have:

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Experienced in using AI tools in day-to-day workflow

Project description:

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Support of complex data, process, and AI transformation programmes (e.g. EFSA context)

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Focus on leveraging AI (including GenAI and Machine Learning) to redesign business processes, enable intelligent decision-making, and deliver scalable AI solutions

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Work within enterprise environments with strong alignment to organisational goals

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Act as a bridge between business stakeholders, data teams, and technical teams

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Ensure successful deployment of AI solutions into production environments

Main responsibilities:

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Drive AI-enabled transformation initiatives across complex business domains

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Elicit, analyse, and document AI use cases, requirements, and business needs

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Lead end-to-end process redesign, integrating AI capabilities to enhance efficiency and decision-making

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Design and support implementation of AI-driven decision models combining human and machine inputs

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Contribute to delivery and deployment of AI components into production environments

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Support integration of AI services within enterprise architectures, including cloud-based solutions (e.g. Azure)

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Perform data-driven analysis with strong focus on data quality, integrity, and governance

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Collaborate with multi-disciplinary stakeholders (business, IT, data teams, external providers)

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Ensure alignment with enterprise standards, governance, and security frameworks

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Provide structured business analysis support across data, process, and AI transformation initiatives

Originally posted on Himalayas