Project Lead - Data & AI

About the role

The Project Lead is responsible for the end-to-end planning, coordination, governance and delivery of Data, Analytics and AI-related projects and strategic initiatives. The role acts as the central delivery focal point between Data & Analytics, business stakeholders, IT teams, Digital Transformation, vendors and governance functions, ensuring initiatives are delivered within scope, timeline and budget.

Key responsibilities

• Lead and finalise project initiation activities, coordinate alignments, committee approvals and endorsements.
• Lead end-to-end delivery of Data, Analytics and AI projects, from initiation through implementation and closure.
• Manage project plans, milestones, budgets, resources, risks, issues and dependencies.
• Coordinate across business, Data Analytics, IT, Digital Transformation, vendors and control functions.
• Drive initiatives covering data platforms, BI/analytics, data engineering, governance, data quality and AI use cases.
• Maintain project governance, including RAID tracking, documentation, approvals and executive status reporting.
• Manage stakeholders and vendors, and coordinate testing, UAT, production readiness and BAU handover.
• Report project health consistently and proactively resolve blockers and escalate risks or delays.

Required profile

• Bachelor's degree in Computer Science, IT, Information Systems, Engineering, Data/Analytics, Business Technology or equivalent.
• 8+ years of overall IT/project delivery experience, 5+ years managing complex technology, data, analytics or digital transformation projects.
• Demonstrable experience coordinating projects across business and multiple IT disciplines; previous exposure to banking or financial services strongly preferred.
• Experience managing external vendors, consultants or outsourced resources, and preparing management-level project status and governance reporting.
• PMP, PRINCE2 or Agile/Scrum certification highly preferred.

Required skills

• Enterprise data warehouse, data platforms, data engineering and ETL/ELT
• Data governance, data quality, BI, dashboards and advanced analytics
• AI/ML project lifecycle and GenAI use cases, data integration and APIs
• Cloud/data platforms, data privacy, security and access controls
• Testing, UAT and production, AI/data readiness and governance concepts