Data & AI Project Manager
Key Responsibilities Project Management Lead end-to-end delivery of Data & AI projects from initiation through deployment and post-production support. Develop project plans, timelines, budgets, resource plans, and risk mitigation strategies. Manage project scope, schedules, dependencies, and deliverables. Data & AI Delivery Coordinate the implementation of AI, Machine Learning, Generative AI, Business Intelligence, and Data Engineering initiatives. Collaborate with data scientists, data engineers, architects, developers, and business stakeholders. Ensure AI solutions meet business requirements, governance standards, and regulatory compliance. Oversee data migration, data quality, master data management, and analytics initiatives. Support AI model deployment, monitoring, and lifecycle management. Stakeholder Management Act as the primary point of contact between business teams, technical teams, and executive leadership. Translate business requirements into actionable project deliverables. Present project status, risks, milestones, and KPIs to senior management. Manage vendor relationships and third-party delivery partners where applicable. Governance & Risk Management Establish project governance frameworks and reporting mechanisms. Identify project risks, issues, and dependencies and implement mitigation plans. Ensure adherence to organizational security, privacy, and compliance standards. Support change management and user adoption initiatives. Continuous Improvement Drive process improvements in project delivery and operational efficiency. Promote Agile best practices and continuous delivery. Capture lessons learned and contribute to organizational project management standards. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, Business, or a related field. 7–12 years of experience in IT project management, including 3+ years managing Data and AI initiatives. Proven experience delivering enterprise-scale Data, Analytics, AI, or Machine Learning projects. Strong understanding of project management methodologies (Agile, Scrum, SAFe, Waterfall, Hybrid). Experience managing cross-functional and geographically distributed teams