AI Business Analyst

Dicetek LLC

Abu Dhabi

On-site

AED 180,000 - 240,000

Full time

12 days ago
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Job summary

Dicetek LLC is seeking a skilled AI Business Analyst to define and frame AI use cases across diverse business units. You will translate complex problems into AI requirements, draft business cases, and collaborate with data scientists and architects to ensure feasible, ethical AI solutions.

You will facilitate cross-functional workshops, communicate AI concepts to non-technical stakeholders, and help shape the organisation's AI playbook and operating model for scalable impact.

Qualifications

  • Bachelor's degree in Business, Computer Science, Data Analytics, or related field.
  • Master's degree is a plus.
  • 3–6 years experience in business analysis, with at least 2 years supporting AI, analytics, or digital transformation projects.
  • Strong understanding of AI concepts including machine learning, NLP, LLMs, vector databases, RAG, and prompt engineering.
  • Experience working within Microsoft's AI and productivity ecosystem (Azure AI, Microsoft 365, Power Platform, Copilot).
  • Proven ability to document and present complex ideas in a clear, executive-friendly format.

Responsibilities

  • AI Use Case Definition & Impact Framing
  • Identify, qualify, and refine AI use cases across business units using structured frameworks and value-mapping techniques.
  • Formulate clear, well-structured problem statements and define success criteria aligned to efficiency, customer experience, or revenue growth.
  • Assess use case feasibility based on technical complexity, data availability, integration needs, and business readiness.
  • Documentation & Analysis
  • Translate complex business problems into AI requirements and solution hypotheses.
  • Prepare high-quality business cases, value assessments, process flows, and technical documentation to support experimentation and implementation.
  • Collaborate with data scientists, solution architects, and platform leads to validate solution approaches and ensure technical fit.
  • Stakeholder Engagement & Communication
  • Facilitate cross-functional workshops with business units, IT, and Digital teams to surface pain points and explore AI opportunities.
  • Clearly communicate AI concepts, limitations, and trade-offs to non-technical stakeholders in a way that drives alignment and action.
  • Act as the voice of the user in solution design — ensuring outcomes are human-centric, ethical, and usable.
  • Critical Thinking & Conceptual Rigor
  • Analyze processes, data flows, and decision points to pinpoint where AI can generate meaningful business impact.
  • Apply systems thinking and root cause analysis to ensure AI interventions are both sustainable and scalable.
  • Evaluate and prioritize ideas using scoring models, effort/impact grids, and strategic alignment checks.
  • AI Knowledge Integration
  • Stay up to date with the latest in generative AI, machine learning, LLMs, semantic search, RPA, and Microsoft AI tools (e.g., Azure AI, Copilot Studio).
  • Contribute to refining the organisation's AI playbook, use case library, and intake methodology.
  • Consider business use case alignment with the organisation's AI operating model and the organisation's enterprise architecture.

Skills

AI concepts
Executive communication
Problem framing
Data-driven decision making

Education

Bachelor's degree in Business, Computer Science, Data Analytics, or a related field
Master's degree is a plus

Tools

Azure AI
Microsoft 365
Power Platform
Copilot

Job description

Required
  • Bachelor's degree in Business, Computer Science, Data Analytics, or a related field.

Master's degree is a plus.

  • 3–6 years experience in business analysis, with at least 2 years supporting AI, analytics, or digital transformation projects.
  • Strong foundational understanding of AI concepts including machine learning, NLP, LLMs, vector databases, RAG, and prompt engineering.
  • Experience working within Microsoft's AI and productivity ecosystem (Azure AI, Microsoft 365, Power Platform, Copilot).
  • Proven ability to document and present complex ideas in a clear, engaging, and executive-friendly format.
Key Responsibilities
  • AI Use Case Definition & Impact Framing
  • Identify, qualify, and refine AI use cases across business units using structured frameworks and value-mapping techniques.
  • Formulate clear, well-structured problem statements and define success criteria aligned to efficiency, customer experience, or revenue growth.
  • Assess use case feasibility based on technical complexity, data availability, integration needs, and business readiness.
  • Documentation & Analysis
  • Translate complex business problems into AI requirements and solution hypotheses.
  • Prepare high-quality business cases, value assessments, process flows, and technical documentation to support experimentation and implementation.
  • Collaborate with data scientists, solution architects, and platform leads to validate solution approaches and ensure technical fit.
  • Stakeholder Engagement & Communication
  • Facilitate cross-functional workshops with business units, IT, and Digital teams to surface pain points and explore AI opportunities.
  • Clearly communicate AI concepts, limitations, and trade-offs to non-technical stakeholders in a way that drives alignment and action.
  • Act as the voice of the user in solution design — ensuring outcomes are human-centric, ethical, and usable.
  • Critical Thinking & Conceptual Rigor
  • Analyze processes, data flows, and decision points to pinpoint where AI can generate meaningful business impact.
  • Apply systems thinking and root cause analysis to ensure AI interventions are both sustainable and scalable.
  • Evaluate and prioritize ideas using scoring models, effort/impact grids, and strategic alignment checks.
  • AI Knowledge Integration
  • Stay up to date with the latest in generative AI, machine learning, LLMs, semantic search, RPA, and Microsoft AI tools (e.g., Azure AI, Copilot Studio).
  • Contribute to refining the organisation's AI playbook, use case library, and intake methodology.
  • Consider business use case alignment with the organisation's AI operating model and the organisation's enterprise architecture.
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