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The Opportunity The Finance Transformation Manager (AI/Task Mining) will lead AI-enabled process transformation across Finance Operations, with a strong focus on Record to Report (R2R), Order to Cash (O2C), and Procure to Pay (P2P). This role will combine finance process expertise, continuous improvement, task and process mining, intelligent automation, and emerging AI capabilities to improve efficiency, scalability, control, and data quality within Finance. You will identify high-value transformation opportunities, translate finance pain points into practical digital solutions, and work cross-functionally with Finance, Product, Data, Engineering, and Technology teams to deliver sustainable outcomes. The successful candidate will help establish a scalable transformation pipeline—from opportunity identification and business-case development through solution design, pilot, implementation, adoption, and benefit realization. In This Role, You Will Lead end-to-end finance transformation initiatives across R2R, O2C, and P2P. Assess processes using process mining, task mining, value-stream mapping, and data analysis to identify inefficiencies, risks, and automation opportunities. Identify, prioritize, and evaluate use cases for GenAI, machine learning, OCR/IDP, RPA, workflow automation, and analytics. Translate Finance pain points into scalable AI-enabled solutions with Finance, Product, Data, Engineering, Technology, Risk, and Compliance teams. Develop business cases, transformation roadmaps, pilot plans, and benefits-tracking frameworks, and project-manage the implementations. Evaluate AI tools, automation platforms, and vendors based on business value, usability, data requirements, scalability, integration complexity, cost, risk, and controls. Lead proofs of concept and support the implementation, adoption, and scaling of successful solutions. Establish appropriate controls for AI-enabled processes, including human oversight, auditability, data quality, privacy, and compliance. Design Finance process-management standards, including process inventories, L3/L4 documentation, ownership models, SOPs, controls, and governance. Define process KPIs, baselines, targets, dashboards, and reporting frameworks in partnership with Data and Technology teams.