AI Business Analyst

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