Business/Data Analyst

KAYGEN•Charlotte, NC

3d•Hybrid

About The Position

KAYGEN is seeking a Business Systems Analyst to join an innovative and high-impact team building AI capabilities within enterprise systems for a leading wealth management client. This is an opportunity to shape the next generation of enterprise AI in a highly visible environment, where innovation, rigor, and business value all matter. The ideal candidate is curious, hands-on, and energized by solving real-world problems at the intersection of AI, enterprise technology, and wealth management. The role involves developing a deep understanding of how enterprise systems, data platforms, and AI services interact and how changes affect firm operations and initiatives. The analyst will partner with stakeholders to define AI use cases and success measures, and document current-state pain points and future-state workflows. They will elicit and translate requirements into actionable specifications, including data readiness, performance, availability, and auditability needs for AI-enabled features. Mapping data structures and elements to business processes, ensuring accurate documentation of data lineage, definitions, usage, and access controls is also a key responsibility. The analyst will create and maintain artifacts such as business process models, data flow diagrams, prototypes, business requirements, use cases/user stories, acceptance criteria, and test cases. Support for AI solution design by documenting model inputs/outputs, decision points, human-in-the-loop steps, and integration patterns is required. Collaboration with data and AI/ML teams on model lifecycle needs, and with risk, privacy, security, and compliance stakeholders to capture AI-related controls and governance requirements is essential. The role also includes executing and presenting written and verbal business systems impact analyses and helping reinforce Business Systems Analyst principles and practices across the team.

Requirements

6+ years of demonstrated experience serving as a Business Systems Analyst, Business Analyst, or similar role
Experience in enterprise-scale AI/GenAI initiatives, with direct involvement in the requirements definition, analysis, and delivery of solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and/or agentic AI capabilities
Proven experience eliciting requirements from business stakeholders and refining those requirements into engineering-ready deliverables that support the successful implementation and adoption of AI-powered products and capabilities.
Experience supporting the implementation of enterprise AI solutions within a regulated financial services environment, including banking, wealth management, or similar.
Strong knowledge of Agile / SAFe Agile delivery methodologies

Nice To Haves

Customer Advocacy skills
Finance industry experience (added advantage)
Ability to balance technical constraints with business objectives.
Comfort making decisions with incomplete information (“bias for action”).
Strong negotiation and conflict resolution skills.

Responsibilities

Develop a deep understanding of how enterprise systems, data platforms, and AI services interact and how changes affect firm operations and initiatives.
Partner with stakeholders to define AI use cases and success measures; document current-state pain points and future-state workflows.
Elicit and translate requirements into actionable specifications (functional and non-functional), including data readiness, performance, availability, and auditability needs for AI-enabled features.
Map data structures and elements to business processes, ensuring accurate documentation of data lineage, definitions, usage, and access controls.
Create and maintain artifacts such as business process models, data flow diagrams, prototypes, business requirements, use cases/user stories, acceptance criteria, and test cases.
Support AI solution design by documenting model inputs/outputs, decision points, human-in-the-loop steps, and integration patterns (e.g., APIs, event streaming, batch pipelines).
Partner with data and AI/ML teams on model lifecycle needs: training/validation data requirements, evaluation criteria, monitoring requirements (e.g., drift, performance), and operational handoffs.
Collaborate with risk, privacy, security, and compliance stakeholders to capture AI-related controls and governance requirements (e.g., data handling, model transparency/explainability expectations, escalation paths).
Execute and present written and verbal business systems impact analyses that identify high-impact, systemic solutions.
Help reinforce Business Systems Analyst principles and practices across the team (standards, templates, requirement quality, and test readiness).