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AI Business Analyst / Product Manager

📅 Jun 16
Stakeholder ManagementWorkshop FacilitationBusiness Process AnalysisRequirements Gathering
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📜 Description

  • Facilitate stakeholder workshops to identify and prioritize AI use cases, develop ROI-based business cases, and build consensus on solution direction.
  • Document current workflows and pain points, redesign processes with appropriate controls, and quantify expected improvements.
  • Translate business needs into technical requirements, user stories, acceptance criteria, and success measures.
  • Build no-code/low-code demonstrations, gather user feedback, and develop prompt templates for financial use cases.
  • Develop AI testing, governance, and model-risk documentation aligned with financial regulations.
  • Apply financial ontologies and knowledge graph integrations, manage stakeholder alignment, and evaluate emerging AI tools.

🛠️ Requirements

  • Stakeholder management and workshop facilitation
  • Business process analysis, requirements gathering, and documentation
  • Project scoping, ROI modeling, and business case development
  • LLM frameworks and prompt engineering for financial applications
  • Hands-on AI tool experience, including no-code/low-code platforms
  • Financial ontologies and graph databases (Neo4j, RDF/OWL)
  • AI governance, testing, and validation in regulated environments
  • 3-5+ years experience in business analysis, process improvement, or consulting
  • Practical implementation experience with LLMs and generative AI
  • Hands-on experience with one or more no-code/low-code platforms
Full job description

Objective

Identify and validate high-value AI opportunities, rapidly prototype solutions, and ensure implementations deliver measurable business outcomes and tangible ROI.

KPI

  • Revenue/cost impact of implemented AI solutions

  • Stakeholders' satisfaction with business case clarity and realization

Areas of Responsibility

  • Lead Discovery Process and Validate AI Opportunities

    • Facilitate stakeholder workshops to identify and prioritize high-impact AI use cases

    • Develop business cases with clear ROI models and success metrics

    • Build consensus among stakeholders on solution direction

  • Map and Redesign Business Processes

    • Document current workflows and pain points

    • Design workflows with appropriate boundaries and controls for financial environments and Agentic AI systems

    • Quantify expected business improvements

  • Define AI Solution Requirements

    • Translate business needs into clear technical requirements

    • Create user stories and acceptance criteria

    • Establish validation approaches for measuring success

  • Create Solution Prototypes

    • Build functional demonstrations using no-code/low-code tools

    • Gather user feedback to refine concepts

    • Develop prompt templates for financial use cases

  • Implement AI Governance and Compliance

    • Develop testing methodologies for AI systems in regulated environments

    • Ensure alignment with financial regulations (e.g US SR 11-7, EU AI Act)

    • Create documentation standards for model risk management

  • Leverage Financial Services Industry (FSI) Ontologies

    • Apply industry-standard financial ontologies (e.g. FIBO) to structure and ground data

    • Design knowledge graph integrations to improve AI accuracy and compliance

    • Validate ontology completeness and accuracy for financial applications

  • Ensure Ongoing Business Alignment

    • Manage stakeholder expectations throughout delivery

    • Lead business review sessions

    • Mitigate risks to value realization

  • Stay Current on AI Capabilities

    • Actively test and experiment with emerging AI technologies firsthand

    • Evaluate new tools and platforms for business value

    • Share relevant insights with stakeholders

Skills

  • Stakeholder management and workshop facilitation

  • Business process analysis, requirements gathering, and documentation

  • Project scoping, ROI modeling, and business case development

  • LLM frameworks and prompt engineering for financial applications

  • Hands-on AI tool experience, including no-code/low-code platforms

  • Financial ontologies and graph databases (Neo4j, RDF/OWL)

  • AI governance, testing, and validation in regulated environments

Traits

  • Strategic business thinker who can identify valuable AI application opportunities

  • Detail-oriented process analyst who can map complex workflows

  • Technically curious with practical, hands-on AI knowledge

  • Exceptional communicator who can translate between technical and business stakeholders

  • Creative problem-solver able to rapidly prototype solutions

  • Client-focused consultant who builds trust and drives business outcomes

Experience

  • 3-5+ years experience in business analysis, process improvement, or consulting

  • Practical implementation experience with LLMs and generative AI

  • Hands-on experience with one or more no-code/low-code platforms

  • Hands-on experience with orchestration frameworks (LangChain, AutoGen) or knowledge graphs

  • Demonstrated success in requirements gathering and stakeholder management

  • Demonstrated success moving AI projects from proof-of-concept to production in regulated environments

  • Experience with digital transformation or technology implementation projects

  • Background in financial services with understanding of regulatory requirement

Terms & conditions

B2B contract, full remote, can be part-time or full-time engagement.

Time zone: Europe

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