Senior Development Lead - Advanced RPA Noida, Uttar Pradesh
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
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