Finance Program Manager

As a Finance Program Manager, you will play a pivotal role in ensuring the successful execution of Finance Transformation initiatives. You will work closely with cross-functional teams, including Finance, Procurement, EIT, HR, external consultancy and other relevant departments and stakeholders across the globe, to oversee program planning, execution, monitoring, and reporting. Your primary goal is to ensure effective planning and execution of assigned programs under the Transformation Portfolio, including programs that identify, pilot, and scale AI solutions (such as generative AI, machine learning, and intelligent automation) across Finance processes. This is a global role. Key Responsibilities: • Program and Project Planning and Management: • Collaborate with stakeholders to define program/project objectives, scope, and deliverables. • Develop comprehensive project plans, including timelines, budgets, and resource requirements. • Prioritizing strategic initiatives within the Program. Managing interdependencies between projects. Ensuring resource capacity and availability. • Coordinate project kick-off meetings, establish communication channels, and assign responsibilities. • Program Governance • Define key success metrics for each program and track progress against these metrics. This provides a quantifiable way to assess and report the success of the projects and the overall transformation initiative. • Oversee the work of assigned Project Managers under the program • AI Implementation Program Management in Finance: • Lead end-to-end delivery of AI initiatives in Finance (e.g., forecasting and planning, close and reconciliation automation, accounts payable/receivable, audit and controls, financial reporting, and GenAI-enabled analysis), from use-case identification through pilot, deployment, and scale. • Partner with Finance process owners, EIT, Data & Analytics, Procurement, Legal, Risk, and external vendors or consultancies to define use cases, build business cases, and prioritize the AI roadmap based on value, feasibility, and risk. • Coordinate data readiness, model development, testing, validation, and integration activities with data science and engineering teams; manage vendor selection and third-party AI solution delivery. • Establish AI governance within the program, including responsible AI principles, model risk management, human-in-the-loop controls, explainability, data privacy, and security requirements, aligned with internal policies and emerging regulations. • Define and track AI-specific success metrics (e.g., efficiency gains, forecast accuracy, cycle-time reduction, cost savings, adoption rates, and realized ROI) and report benefits realization to senior management. • Drive change management and adoption, including training, communications, and workforce enablement, so that Finance teams can effectively use and trust AI-enabled tools and processes. • Monitor the evolving AI landscape and share lessons learned and reusable assets (playbooks, templates, and standards) across the Transformation Portfolio. • Financial Analysis and Reporting: • Monitor project financials, including budgets, expenses, and forecasts. • Prepare and analyze financial reports, identifying variances and recommending corrective actions. • Ensure financial compliance and adherence to project budgets. • Risk Management: • Identify project risks and develop mitigation strategies. • Proactively address issues and obstacles that may impact project success. • Maintain a risk register and update it regularly. • Identify and manage AI-specific risks, including data quality, model bias, hallucination, explainability, third-party/vendor dependency, and cybersecurity and privacy exposure. • Stakeholder Communication: • Maintain clear and open communication channels with project stakeholders. • Provide regular project status updates and reports to senior management. • Address stakeholder concerns and provide solutions as needed. • Process Improvement: • Continuously assess and improve project management processes and methodologies. • Identify opportunities to enhance efficiency and effectiveness in project delivery. • Implement best practices in project management. • Documentation and Compliance: • Ensure that all project documentation is complete and organized. • Monitor compliance with internal policies, industry regulations, and standards. • Assist in audit preparations and responses. • Ensure AI solutions are documented, validated, and auditable, and that they comply with responsible AI, model risk management, and applicable regulatory requirements (e.g., EU AI Act, SOX).