Business Analyst - Data & AI Practice

Description
The Business Analyst (Data & AI) serves as the bridge between business stakeholders and technical delivery teams. This role works directly with clients to understand their business objectives, operating models, business processes, challenges, and opportunities for improvement. The Business Analyst identifies where data, analytics, automation, and artificial intelligence can create measurable business value and translates those opportunities into actionable requirements for solution architects, engineers, and developers.

This position requires a strong combination of business acumen, process analysis, stakeholder engagement, and technology awareness. The ideal candidate is naturally curious, asks insightful questions, and enjoys understanding how businesses operate.

Key Responsibilities

Business Discovery & Process Analysis

Lead workshops, interviews, and discovery sessions with executive, operational, and technical stakeholders.
Document current-state business processes, workflows, systems, and decision-making activities.
Analyze business operations to identify inefficiencies, bottlenecks, risks, and opportunities for improvement.
Develop process maps, workflow diagrams, user journeys, and business capability models.
Understand organizational goals, KPIs, and business drivers.

AI & Data Opportunity Identification

Evaluate business processes to identify opportunities for:
Artificial Intelligence
Machine Learning
Generative AI
Process Automation
Data Analytics
Predictive Modeling
Intelligent Document Processing
Quantify potential business value, including:
Cost reduction
Productivity gains
Revenue growth
Risk mitigation
Customer experience improvements
Assist clients in prioritizing use cases based on business impact, feasibility, complexity, and ROI.

Requirements Gathering & Documentation

Gather, document, and validate business, functional, and non-functional requirements.
Create user stories, use cases, acceptance criteria, and process documentation.
Translate business needs into requirements that can be consumed by data engineers, AI engineers, architects, and developers.
Facilitate stakeholder reviews and approval processes.

Client Engagement

Build trusted advisor relationships with client stakeholders.
Facilitate workshops ranging from executive strategy discussions to operational process reviews.
Present findings, recommendations, and business cases to leadership teams.
Help clients understand AI capabilities, limitations, risks, and implementation considerations.
Solution Planning & Delivery Support

Requirements
Required Qualifications

Bachelor's degree in Business, Information Systems, Data Analytics, Operations Management, or related field, or equivalent experience.
3–7 years of experience as a Business Analyst, Process Analyst, Management Consultant, or similar role.
Strong experience conducting stakeholder interviews and business process analysis.
Experience documenting requirements, workflows, and business processes.
Strong communication and presentation skills.
Ability to facilitate workshops and lead discovery sessions.
Experience working with cross-functional business and technical teams.

Preferred Qualifications

Experience with Data & Analytics initiatives.
Experience with AI, Generative AI, Machine Learning, or Intelligent Automation projects.
Knowledge of process improvement methodologies such as Lean, Six Sigma, or Value Stream Mapping.
Familiarity with Microsoft Fabric, Azure AI, Power BI, Copilot, Azure OpenAI, or similar platforms.
Experience developing business cases and ROI models.
Consulting or professional services experience.

Key Skills

Business Skills

Business Process Analysis
Requirements Gathering
Stakeholder Management
Workshop Facilitation
Strategic Thinking
Business Case Development
Change Management

Technical Awareness

Data Analytics
AI & Generative AI Concepts
Process Automation
Data Governance
Reporting & Visualization
Enterprise Applications

Soft Skills

Curiosity and critical thinking
Strong questioning and listening skills
Executive presence
Problem-solving mindset
Relationship building
Ability to simplify complex concepts

Success Metrics

The successful candidate will be measured on:

Number of business discovery engagements completed
AI and automation opportunities identified
Estimated and realized business value generated
Client satisfaction scores
Quality and completeness of requirements documentation
Adoption and success of delivered AI and data solutions
Contribution to pipeline generation and expansion opportunities