Senior Manager, AI & Analytics

Role & responsibilities

AI & Analytics Delivery
• Lead business-driven analytics and AI initiatives that support Finance priorities. • Review and assess new AI ideas, run feasibility reviews, and lead proof-of-concept work in controlled sandbox environments to confirm value and ROI. • After validation, work with technology teams for implementation and production rollout. • Design and deliver BI and reporting solutions end-to-end, including dashboards, KPIs, and self-service reporting, with tech support as needed. • Drive modernization and simplification of Finance reporting to improve speed, accuracy, and transparency. • Use enterprise tools such as Microsoft Fabric, Databricks, Denodo, and Power BI to deliver insights that support forecasting, allocations, planning, and performance management.

Cross-Pillar Collaboration
• Partner with the Data Strategy (VISTA) and Process Reengineering (POET) teams to deliver integrated data, process, and analytics solutions. • Work with GCC Finance, Technology, Platform Engineering, AI CoE, HUB, and Enterprise Architecture to ensure scalable and compliant delivery. • Maintain strong cross collaboration between teams for alignment and reuse of analytics and AI assets.

Governance & Value Realization
• Apply standards for responsible AI use, documentation, and governance. • Track and report outcomes such as shorter cycle times, higher forecast accuracy, and reduced manual effort. • Protect sensitive finance data and uphold enterprise privacy and control requirements.

Leadership & Capability Building
• Manage and coach a 57-member team of data scientists, BI developers, and automation specialists. • Build local capability in analytics and automation through training and mentorship. • Promote a culture of innovation and continuous improvement across the Finance Data Office.

Qualification & Experience

•13-16 years in analytics, data science, or business intelligence with at least 5 years in a leadership or lead role.
• Experience delivering analytics or automation initiatives for Finance or FP&A functions. • Knowledge of finance data domains such as general ledger, allocations, forecasting, and planning. • Strong skills in tools like Power BI, Databricks, Microsoft Fabric, and Denodo. • Familiarity with AI/ML frameworks (Python, TensorFlow, Azure ML) and emerging GenAI and automation tools. • Experience managing teams across geographies and collaborating across time zones. • Certifications such as Azure AI Engineer or Data Science Professional are a plus. • Strong communication and stakeholder management skills.