Business Analyst - Data & AI Practice

Role Overview

The Business Analyst for the Data & AI practice acts as the link between business stakeholders and technical delivery teams. In this role, you will work with clients to learn their goals, operating structures, business processes, pain points, and improvement opportunities. You will also identify where data, analytics, automation, and artificial intelligence can deliver measurable business outcomes and convert those opportunities into clear requirements for solution architects, engineers, and developers.

The position calls for a blend of business understanding, process analysis, stakeholder management, and comfort with technology. The right candidate will be naturally inquisitive, ask thoughtful questions, and enjoy learning how organizations operate.

Business Discovery & Process Analysis

• Run workshops, interviews, and discovery sessions with executive, operational, and technical stakeholders.
• Capture the present-state of business workflows, systems, decision paths, and operating processes.
• Review business operations to spot inefficiencies, delays, risks, and improvement opportunities.
• Create process maps, workflow diagrams, user journeys, and business capability models.
• Understand organizational goals, KPIs, and the main business drivers behind them.

AI & Data Opportunity Identification

• Assess business processes to find opportunities for artificial intelligence, machine learning, generative AI, process automation, data analytics, predictive modeling, and intelligent document processing.
• Estimate possible value from each opportunity, including lower costs, higher productivity, revenue growth, reduced risk, and better customer experience.
• Help clients rank use cases by business impact, feasibility, complexity, and return on investment.

Requirements Gathering & Documentation

• Collect, record, and confirm business, functional, and non-functional requirements.
• Prepare user stories, use cases, acceptance criteria, and process documentation.
• Convert business needs into requirements that can be used by data engineers, AI engineers, architects, and developers.
• Support stakeholder review cycles and approval steps.

Client Engagement

• Develop trusted advisor relationships with client stakeholders.
• Lead discussions that range from executive strategy conversations to detailed operational process reviews.
• Present findings, recommendations, and business cases to leadership teams.
• Help clients understand what AI can do, its limitations, associated risks, and implementation considerations.

Solution Planning & Delivery Support

• Work with solution architects and AI engineers to ensure business needs align with technical designs.
• Support delivery teams during solution design and implementation.
• Take part in testing, validation, and user acceptance activities.
• Assist with change management, adoption planning, and business readiness efforts.

Required Qualifications

• Bachelor’s degree in Business, Information Systems, Data Analytics, Operations Management, or a related area, or equivalent experience.
• 3 to 7 years of experience in a Business Analyst, Process Analyst, Management Consultant, or similar position.
• Strong background in stakeholder interviews and business process analysis.
• Experience documenting requirements, workflows, and business processes.
• Excellent communication and presentation abilities.
• Ability to facilitate workshops and lead discovery sessions.
• Experience collaborating with cross-functional business and technical teams.

Preferred Qualifications

• Experience supporting data and analytics initiatives.
• Exposure to AI, generative AI, machine learning, or intelligent automation projects.
• Knowledge of process improvement methods such as Lean, Six Sigma, or Value Stream Mapping.
• Familiarity with Microsoft Fabric, Azure AI, Power BI, Copilot, Azure OpenAI, or similar tools and platforms.
• Experience building business cases and ROI models.
• Background in consulting or professional services.

Key Skills

• Business process analysis
• Requirements elicitation
• Stakeholder engagement
• Workshop facilitation
• Strategic thinking
• Business case development
• Change management
• Data analytics awareness
• AI and generative AI concepts
• Process automation
• Data governance
• Reporting and visualization
• Enterprise applications
• Critical thinking
• Executive communication
• Relationship building

Success Metrics

Performance in this role will be assessed by the number of discovery engagements completed, the AI and automation opportunities identified, the business value estimated and delivered, client satisfaction, the quality and completeness of requirements documentation, the adoption and success of AI and data solutions, and contribution to pipeline generation and expansion opportunities.