Head of Analytics

Job Purpose

The Head of Advanced Analytics will establish and lead Americana’s Advanced Analytics Center of Excellence (CoE), driving the adoption of advanced analytics, artificial intelligence, machine learning, and data-driven decision-making across the organization.

This role will build and lead a high-performing analytics team while developing scalable data and analytics capabilities that unlock value from customer, operational, commercial, financial, and workforce data. Partnering closely with senior leaders across the business, the role will deliver actionable insights, predictive models, and AI-driven solutions that improve business performance, operational efficiency, customer experience, and strategic decision-making.

Key Responsibilities

Advanced Analytics Leadership

• Establish and lead the Advanced Analytics Center of Excellence (CoE), defining the analytics vision, strategy, roadmap, governance, and operating model.
• Build, lead, and develop a high-performing team of Data Scientists, Analysts, Data Engineers, and Visualization Specialists.
• Drive the adoption of advanced analytics, artificial intelligence, machine learning, and data-driven decision-making across the organization.
• Act as the organization's subject matter expert on advanced analytics, AI, forecasting, and optimization.

Analytics & AI Solutions

• Develop and deploy advanced analytics, forecasting, optimization, and AI solutions that drive business growth, operational efficiency, and profitability.
• Lead analytics initiatives across Customer & Growth, Marketing ROI, Personalization, Sales Forecasting, Pricing & Menu Optimization, Promotions Effectiveness, Workforce Planning, Logistics Optimization, and Store Operations.
• Deliver predictive and prescriptive insights that improve customer acquisition, retention, revenue growth, margin optimization, operational performance, and workforce productivity.
• Ensure analytics outputs are actionable, commercially relevant, and aligned with strategic business priorities.

Enterprise Data & Analytics Foundations

• Establish scalable, high-quality data foundations that enable advanced analytics and AI initiatives.
• Lead the integration of customer, operational, commercial, financial, digital, delivery, and workforce data across enterprise platforms.
• Define and govern enterprise KPIs, business metrics, data standards, and data quality frameworks.
• Ensure consistency, integrity, and alignment across source systems, analytical models, and reporting environments.
• Support the development of an enterprise-wide analytics architecture that enables self-service analytics and scalable decision intelligence.

Business Partnership & Decision Intelligence

• Partner with senior stakeholders to identify, prioritize, and deliver high-value analytics and AI opportunities.
• Lead analytics initiatives from problem definition through implementation, adoption, and value realization.
• Establish experimentation and testing frameworks, including A/B testing, to support evidence-based decision-making.
• Drive adoption of analytics products, insights, dashboards, and decision-support tools across the business.
• Measure and communicate business impact generated through analytics and AI initiatives.

Governance & Best Practices

• Define standards and best practices for analytics development, machine learning deployment, experimentation, model governance, and analytics documentation.
• Ensure compliance with data privacy, security, governance, and responsible AI principles.
• Partner with Technology, Data Engineering, and IT teams to ensure sustainable, scalable, and secure analytics capabilities.

Team Leadership & Capability Building

• Recruit, coach, mentor, and develop high-performing analytics talent.
• Build future-ready capabilities across analytics, forecasting, data science, m