AI Business Analyst

Role Overview

• Lead structured discovery workshops with client stakeholders — using AI tools in session to capture, synthesize, and reflect back current-state processes, pain points, and desired outcomes in real time; produce structured outputs before the debrief.
• Conduct process and task mining analysis using Microsoft Process Mining, Celonis, or equivalent platforms to surface high-ROI automation opportunities; translate event-log insights into prioritized opportunity backlogs with quantified business impact.
• Analyze UX feedback, job aids, procedures, and existing process maps to identify candidates for further optimization; summarize findings and present recommendations with supporting data.
• Proactively identify, analyze, and resolve requirement risks, gaps, and ambiguities — using LLM-assisted cross-reference of documentation to catch inconsistencies before they reach development; partner with stakeholders to resolve issues and appropriately escalate matters when additional guidance or decisions are required.
• Elicit and document business, user, functional, and non-functional requirements with sufficient detail to support effective implementation of AI-enabled and traditional technology solutions — including decision logic, tool invocations, exception handling, and appropriate human review and oversight checkpoints.
• Translate requirements into the full artifact set: user stories, acceptance criteria, process flows, wireframes, data models, swimlane diagrams, and state diagrams — using AI-assisted tooling to accelerate first-draft creation and human judgment to validate and refine.
• Design Target Operating Models that show how people, AI agents, and automated processes interact in the future state — including role evolution, governance guardrails, and escalation paths that keep humans accountable for outcomes.
• Use AI coding and analysis assistants (Claude Code, Codex, Copilot Cowork) as a productivity layer: generate first drafts of plans, criteria, models, and documentation; ensure all deliverables meet quality, accuracy, and business requirements.
• Own requirements traceability end-to-end and maintain alignment between business requirements, solution design, testing activities, and expected business outcomes; maintain documentation throughout the project lifecycle to reflect evolving business needs and decisions.
• Lead backlog organization, refinement, and work item maintenance using Crowe-standard Agile tooling (Azure DevOps or equivalent) — ensuring stories are sprint-ready, acceptance criteria are complete, and the backlog reflects current business priorities at all times.
• Build and execute structured testing programs — functional, integration, regression, performance, and usability — for Gen AI solutions from first prototype through production handoff; prepare test plans and scripts with enough specificity that a QA engineer can execute them without clarification.
• Facilitate and lead User Acceptance Testing (UAT): coordinate test cycles with client teams, manage defect triage, and own sign-off on solution readiness.
• Build audience-calibrated presentation materials and present findings, recommendations, and ROI narratives to executives, operational leads, and end users — adjusting depth and framing without losing substance or precision.
• Apply and uphold Crowe BA standards, templates, and best practices; identify where AI-augmented delivery requires those standards to evolve and contribute to their improvement.
• Actively develop your own practice — through emerging AI tooling, peer feedback, and client exposure — and share what you learn with the broader BA community at Crowe.

Requirements

• 1
• 3 years in business analysis, process optimization, or hyperautomation delivery with direct exposure to AI/ML or Gen AI solution delivery
• Demonstrated daily use of Gen AI tools — Claude Code, Codex, Copilot Cowork, or equivalent
• Full requirements artifact ownership — proven track record producing complete artifact set: user stories, acceptance criteria, process flows, wireframes, data models, and traceability matrices for software or AI-powered solution delivery
• Agile delivery fluency — user story authoring, sprint facilitation, backlog refinement, and acceptance criteria definition in Azure DevOps, Jira, or equivalent
• Risk and gap analysis — ability to identify and address requirement inconsistencies, dependencies, risks, and scope considerations throughout the delivery lifecycle
• English communication at full professional proficiency** — written precision and spoken clarity enabling peer-level dialogue with US-based executives and technical leads across time zones, within a global delivery environment.
• Foundational Bachelor's degree in Business, Information Systems, Computer Science, Engineering, or a related field; equivalent experience considered
• Analytical mindset with the ability to break down complex, ambiguous problems into structured, actionable components
• Willingness to maintain a core overlap window of approximately 6:30 PM – 12:30 AM IST for US Central/Eastern collaboration

Tech Stack

• Azure

Benefits

• Comprehensive benefits package
• Health insurance
• Flexible work arrangements
• Professional development opportunities