Senior Business Analyst

LSEG Business Services RM; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

LSEG Business Services RM is seeking a Senior Business Analyst to bridge business needs and AI/ML solution delivery in Bengaluru. You will translate requirements for AI/Agentic AI projects, define epics and user stories, and collaborate with Data Scientists and AI Engineers to ensure objective-aligned outcomes.

You will also support data analysis, model evaluation, and governance documentation for responsible AI, while coordinating with risk and security teams to ensure compliant, auditable

Qualifications

• Bachelor's or higher degree in a relevant field is required.
• Minimum 5 years of professional BA experience in tech or data-driven projects.
• Strong requirements gathering, documentation, and agile delivery skills.

Responsibilities

• Gather, analyse, and document requirements for AI/ML and Agentic AI solutions.
• Translate business needs into technical requirements, epics, and user stories with acceptance criteria.
• Collaborate with Data Scientists and AI Engineers to ensure alignment with business objectives.
• Support data analysis, model evaluation, and governance documentation for responsible AI.
• Define non-functional requirements, risk controls, and auditability alongside architects.

Skills

Business Analysis

Requirements gathering

User stories

Acceptance criteria

Stakeholder management

Agile delivery

Data-driven projects

Education

Bachelor's degree in Business Administration, Information Systems, Computer Science, Information Technology, Engineering, Data Science, Mathematics, Statistics, or a related discipline.

Job description

Senior Business Analyst

Job Description Summary

The Business Analyst will work closely with Data Science, AI Engineering, Product Owners, and business teams to support the development and delivery of AI/ML and Agentic AI solutions. The role involves understanding business requirements, translating them into detailed user stories, and collaborating with Data Scientists and development teams to ensure solutions meet business objectives. The Business Analyst will support AI use case identification, data analysis, requirements documentation, model evaluation, and Agile delivery activities. The role requires strong analytical capabilities, technical understanding, and an interest in emerging AI technologies, particularly Generative AI and Agentic AI. The role also supports AI-specific non-functional requirements, Responsible AI controls, risk identification, and governance documentation.

Key Responsibilities

1. Business Requirements and Analysis

   Engage with business stakeholders to gather, analyse, and document requirements for AI/ML and Agentic AI solutions. Translate business needs into well-defined technical requirements for Data Science team, multiple Epics, user stories, and acceptance criteria. Work with Data Scientists and AI Engineers to understand business rules, data requirements, expected outputs, and solution workflows. Define business scenarios, exception handling, and success criteria for AI-driven solutions. Ensure requirements are clearly documented, testable, and aligned with business objectives.

2. Data Science and Agentic AI Collaboration

   Work closely with Data Science teams to support the development and implementation of AI/ML models and Agentic AI workflows. Understand AI solution workflows, including data extraction, processing, validation, and decision-making. Support the definition of requirements for AI agents, including agent responsibilities, workflow orchestration, tool interactions, and human-in-the-loop processes. Collaborate with technical teams to identify data dependencies, integration requirements, and potential solution limitations. Assist in identifying opportunities for process automation and efficiency improvements using AI technologies.

3. Data Analysis and AI Evaluation

   Support data analysis, data preparation, and validation activities required for AI/ML solutions. Coordinate with business teams to define sampling methodologies and prepare representative Golden Datasets for model training and evaluation. Work with Data Scientists to define evaluation criteria and business success metrics, including precision, recall, accuracy, and automation rates, where applicable. Support model output validation, error analysis, and identification of improvement opportunities. Analyse discrepancies between expected and actual AI outputs and coordinate corrective actions with relevant teams. Support business acceptance testing and ensure AI solutions satisfy agreed success criteria.

4. Responsible AI, Risk & Governance

   Ensure requirements consider data privacy, security, bias, fairness, explainability, transparency, and appropriate human oversight. Work with Data Science, Security, Risk, and Compliance teams to identify, document, and track AI-related risks and mitigating controls. Support AI governance and model approval documentation, risk assessments, and auditability, including decision traceability, access controls, logging, and monitoring. Capture risks including hallucinations, data leakage, prompt injection, model drift, and unintended agent actions; document guardrails, human review, fallback, and escalation requirements in acceptance criteria.

5. Technical Understanding, API Testing & NFRs

   Analyse existing systems, data structures, and workflows to support AI solution integration. Understand and document data schemas, data mappings, JSON, XML/XSD, and API integration requirements. Use Postman or similar API testing tools to inspect and validate API requests, responses, and integrations alongside engineering and QA teams. Prepare process flow diagrams, data flow diagrams, functional specifications, and technical requirement documentation. Define measurable AI/ML and GenAI-specific NFRs with architects and engineers, covering latency, scalability, reliability, security, output quality, robustness, monitoring, explainability, auditability, privacy, and human oversight. Maintain requirements, user stories, acceptance criteria, and project documentation using Jira and Confluence.

Required Knowledge and Skills

Education and Experience

Bachelor's degree in Business Administration, Information Systems, Computer Science, Information Technology, Engineering, Data Science, Mathematics, Statistics, or a related discipline.

Minimum 5 years of professional experience as a Business Analyst, including requirements gathering, process analysis, user stories, acceptance criteria, stakeholder management, and Agile delivery for technology or data-driven projects.

Business Analysis

Good understand