Job Summary

Business Analyst – AI Practice

We are looking for a seasoned Business Analyst with hands-on experience on AI/ML and data projects to join our AI Practice at Band 2.2. You will act as the critical bridge between business stakeholders and AI delivery teams — translating complex business problems into structured requirements, validating AI-driven solutions, and ensuring that delivered models and platforms create measurable business value.

This role requires a blend of strong analytical thinking, domain knowledge, and a working understanding of how AI/ML solutions are built and deployed in enterprise environments.

Key Responsibilities

KEY RESPONSIBILITIES 

Requirements & Discovery

• Facilitate workshops with business stakeholders to elicit, document, and prioritise requirements for AI/ML solutions
• Translate ambiguous business problems into well-structured problem statements, use cases, and acceptance criteria
• Conduct as-is process mapping and identify AI intervention points with measurable ROI
• Define data requirements: sources, quality standards, labelling needs, and feature specifications for ML models

AI Solution Analysis & Validation

• Collaborate with data scientists and ML engineers to validate that model outputs align with business expectations
• Design and execute User Acceptance Testing (UAT) for AI-powered applications including GenAI and NLP tools
• Develop evaluation frameworks: KPIs, model performance metrics tied to business outcomes
• Identify edge cases, bias risks, and explainability needs; escalate findings through appropriate governance channels

Stakeholder Management & Communication

• Serve as the primary liaison between client business teams and HCLTech AI delivery squads
• Prepare and present business requirement documents (BRDs), functional specifications, and solution walkthroughs
• Manage stakeholder expectations, track change requests, and maintain a requirements traceability matrix

Data & Process Analysis

• Perform exploratory data analysis to assess data readiness, completeness, and suitability for AI modelling
• Map and document data flows, pipelines, and integration points across enterprise systems
• Partner with data engineers to define data ingestion, transformation, and governance requirements

Delivery Support

• Work in Agile/Scrum delivery models — write user stories, manage backlogs, and facilitate sprint ceremonies
• Support project managers on scope definition, effort estimation, and risk identification
• Contribute to post-go-live reviews and continuous improvement cycles

Skill Requirements

REQUIRED QUALIFICATIONS & EXPERIENCE 

Experience

• 7 – 10 years of total experience with at least 3 years directly on AI/ML, data analytics, or GenAI projects
• Demonstrated experience in requirements gathering, process analysis, and solution validation on technology programmes
• Prior exposure to consulting or client-facing delivery environments preferred

Technical & Domain Knowledge

• Working understanding of AI/ML concepts: supervised/unsupervised learning, NLP, LLMs, computer vision, recommendation engines
• Familiarity with Generative AI tools and use cases: chatbots, document processing, content generation, code assist
• Ability to write and run basic SQL queries for data exploration and validation
• Experience with BI/analytics tools: Power BI, Tableau, or similar
• Understanding of cloud data platforms: Azure, AWS, or GCP (certification a plus)
• Knowledge of data governance, privacy (GDPR/PDPA), and AI ethics basics

Soft Skills

• Excellent written and verbal communication — ability to simplify complex AI concepts for non-technical audiences
• Strong facilitation and stakeholder management skills
• Detail-oriented with strong analytical and problem-solving mindset
• Self-starter who thrives in ambiguous, fast-paced environments

Education & Certifications

• Bachelor's degree in Engineering, Computer Science, Business, Statistics, or related field
• Certifications in Business Analysis (CBAP, PMI-PBA) or Agile (CSM, PSPO) are preferred
• AI/ML or cloud certifications (Azure AI Fundamentals, AWS Cloud Practitioner, Google AI Essentials) are a plus

  PREFERRED ATTRIBUTES 

• Industry exposure in BFSI, Healthcare, Retail, or Manufacturing contexts for AI solutions
• Experience with LLM-based solution design: RAG pipelines, prompt engineering, agentic workflows
• Exposure to MLOps concepts: model versioning, drift monitoring, retraining pipelines
• Prior experience in a technology consulting or systems integration firm

Other Requirements