Data and AI Project Manager

As a Data & AI Project Manager, you will lead end-to-end delivery of Data, Analytics, and AI engagements—owning governance, financials, scope, schedule, and stakeholder alignment across clients and IBM teams. You’ll drive disciplined execution, proactive risk management, and ensure outcomes are delivered predictably and professionally.

Key Responsibilities

* Lead delivery governance across one or multiple workstreams: plan, RAID, cadence, milestones, dependencies, resourcing

* Own project controls: scope/change control, budget tracking, forecasting, and delivery reporting

* Drive stakeholder management across client leaders, partners, and IBM technical teams; facilitate decisions and remove blockers

* Own risk management: maintain RAID logs, identify delivery/commercial/operational risks early, implement mitigation/contingency plans, and manage escalations to closure

* Maintain delivery quality and client satisfaction; ensure governance actions are tracked and completed

* Build and coach high-performing teams; promote consistent ways of working and continuous improvement

Required Professional and Technical Expertise

* Minimum 10+ years of project/program management experience, delivering complex enterprise initiatives end-to-end

* Proven track record managing multi-stakeholder, high-complexity projects (Agile / hybrid)

* Strong stakeholder management and communication—from technical teams to senior executives

* Experience delivering Data & AI / Analytics / Data Platforms (e.g., data engineering, governance, BI, AI/ML initiatives)

* Strong project controls including financial management, reporting, change control, and risk/issue management (RAID)

Preferred Professional and Technical Expertise

* Certifications for project/program management: Project or program certifications including but not limited to PMP, CMMI, Scrum Master or Agile Project Management.

* Technology Expertise: Experience working with a broad spectrum of technology solutions including Data and AI, Automation, Sustainability, Security, Cloud technologies.