We are seeking a forward-thinking Director of Business Reporting, Advanced Analytics & AI to serve as the strategic architect and operational leader of our enterprise data-to-value ecosystem. This role will define and execute our vision across Business Intelligence, Data Engineering, andour AI Center of Excellence (CoE).
You will lead the transformation from traditional reporting to a modern, AI-powered enterprise, embedding predictive analytics and Generative AI (GenAI) into core business processes. This leader will ensure AI is not just exploratory, but a scalable, governed, and measurable driver of business value.
Responsibilities
1. AI Center of Excellence (CoE) & GenAI Transformation
- Strategic AI Roadmap: Lead the design and deployment of the enterprise AI strategy, prioritizing GenAI, LLM integration, and "Agentic" workflows that automate complex business processes.
- Responsible AI Governance: Establish the framework for ethical AI, including bias mitigation, data privacy, and security protocols in partnership with Legal and Risk teams.
- Value Orchestration: Develop a "Value Realization" framework to move AI use cases from Proof of Concept (PoC) to full-scale production with measurable ROI.
- Democratization: Lead the rollout of "AI Copilots" and natural-language querying tools, enabling non-technical users to interact with data conversationally.
2. Advanced Analytics & Machine Learning
- Predictive/Prescriptive Engine: Direct the data science team in building ML models for demand forecasting, supply chain optimization, and churn prediction.
- Model Lifecycle Management (MLOps): Ensure all models are monitored for "drift" and maintained for long-term accuracy and reliability.
3. Enterprise Business Intelligence & Reporting
- Metric Standardization: Serve as the "Single Source of Truth" gatekeeper, ensuring consistent KPI definitions across global business units.
- Self-Service Evolution: Transition the organization from "request-and-build" static reports to dynamic, self-service environments using Power BI/Qlik.
4. Data Engineering & Cloud Infrastructure (The Foundation)
- Snowflake Ecosystem: Oversee the architecture and cost-optimization of the Snowflake Data Cloud.
- Modern Data Stack (MDS): Direct the use of dbt, Talend, and orchestration tools to ensure data is "AI-ready" (clean, labeled, and accessible).
5. Strategic Leadership & Talent
- Change Management: Act as a primary evangelist for data literacy, helping the organization overcome resistance to AI adoption.
- Team Building: Coach a multidisciplinary team of Data Engineers, BI Developers, and Data Scientists, fostering a culture of rapid experimentation.