Scrum Master - AI & Data Practice

An internal Scrum Master to support end-to-end operations of AI & data practice at VTS. Partners with tech leads, product owners, sales directors, and other internal stakeholders to keep scope, prototypes, schedule, and risks under control while ensuring clear communication and strong execution.Requirements Bachelor's in Engineering, CS, Business, MBA or related field 3-5 years in Scrum Master project coordination, PMO, or junior PM roles Clear written and verbal communication with strong stakeholder engagement Proficient with Azure DevOps or Jira, and collaboration tools (Confluence/Notion) Comfortable building lightweight dashboards (Power BIor equivalents) for KPIs Certifications are a plus: Scrum Master, PMP, PRINCE2,or Agile PM Familiar with Agile and hybrid delivery in consulting orproduct environments Comfortable translating business goals into epics, userstories, and acceptance criteria Exposure to data and ML workflows, cloud platforms,and modern web delivery Able to coordinate multi‑disciplinary squads acrossengineering, data, and design Pre-sales AI and Data operations Run standups, sprint planning, reviews, and retros.Maintain sprint health and cadence Own backlog hygiene: story readiness, prioritisation,dependencies, and acceptance criteria Track timelines, milestones, budgets, RAID (Risks,Assumptions, Issues, Dependencies) Facilitate decision forums and unblock squads byescalating with context Stakeholder management Prepare concise weekly status, burn‑up/down, and riskswith mitigations Coordinate demos, UAT cycles, and sign‑offs. Capturedecisions and actions Align scope across internal stakeholders, managechange requests Quality and governance Ensure definition of ready/done, test plans, and releasechecklists are followed Support compliance with security, privacy, and datagovernance requirements Help enforce AI and Data playbooks, templates, anddocumentation standards Commercials and resourcing Assist with statements of work, estimates, and invoicingsupport Track resource utilisation, capacity, and internalcoordination Delivery Outcomes Reliable sprint throughput and predictable releases Transparent status and risks for leadership and clients On‑time delivery against scope with controlled change and traceability