AI Business Analyst - QA, Officer
State Street Corporation (company site, opens in a new tab)10–12 yrsHyderabadOn-siteDirect career pageEst. 28–45 LPA
Posted 15h ago
Reach people at State Street Corporation
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at State Street Corporation you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Analyze operational data from ServiceNow, Jira, telemetry, and databases to identify bottlenecks, misalignments, and stability patterns in SaaS operations and QA environments.
- Develop dashboards, reports, and business narratives translating findings into actionable remediation steps, automation backlog items, and process improvements.
- Collaborate across AI initiatives to define practical use cases that improve operations and deployment readiness while ensuring compliance with responsible AI governance.
Minimum Requirements
- 10-12 years of experience in Business Analysis or equivalent field.
- Strong background in cloud technologies preferred; experience in software delivery, release management, DevOps, QA, or operational process improvement mandatory.
- Hands-on experience with ServiceNow, Jira, or similar enterprise workflow and ticketing platforms.
- Experience in AI prompt creation, data interrogation, translating technical findings into business deliverables; understanding of responsible AI governance and data compliance.
Ideal Candidate Profile
- Experienced in complex operational and SaaS environment analysis, skilled at correlating multi-source data to diagnose and anticipate operational risks.
- Ability to work independently in ambiguous environments by defining problems, validating data, and driving actionable insights.
- Familiar with AI-enabled delivery practices and responsible AI frameworks, capable of bridging technical and business teams effectively.