Director, Business Reporting, Advanced Analytics & AI

Company Description

For nearly 70 years, MasterBrand has been shaping the places where people come together, enriching lives and creating meaningful memories for our customers. That, combined with our stylish products, expansive dealer and retail network, and dedicated associates, has helped make us the number one North American residential cabinet business. Our unique culture of continuous improvement is based on trusting the tools, empowering the team and moving forward, and is kept alive by our more than 14,000 associates across 20 plus manufacturing facility and offices. Visit www.masterbrand.com to learn more and join us in building great experiences together!

Job Description

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.

Qualifications

• 12+ years of experience in Data, Analytics, or Technology, with at least 5 years in a leadership role
• Demonstrated success leading enterprise AI/ML initiatives, including at least two scaled deployments delivering measurable business impact
• Deep understanding of Generative AI (LLMs, RAG architecture, prompt engineering) and traditional machine learning techniques
• Strong architectural mindset with the ability to connect technical solutions to business outcomes and executive priorities
• Expertise in cloud ecosystems (Azure or AWS), including AI/ML services and data platforms
• Proven ability to influence senior leaders and drive adoption of complex technology initiatives
• Experience integrating enterprise platforms (e.g., Oracle ERP, Salesforce) to enable unified data and insights (Customer 360)
• Familiarity with modern data ecosystems including Snowflake, dbt, Talend, and BI tools (Power BI, Qlik)
• Understanding of data fabric principles and enterprise data architecture stra