Senior Manager Advanced Analytics

Overview

Key Responsibilities

• **Build and Lead the Advanced Analytics Function**
• Establish and lead Americana’s Advanced Analytics Center of Excellence.
• Define the analytics vision, roadmap, and operating model.
• Recruit, develop, and lead a high-performing team including:
• Data Scientists
• Advanced Analysts
• Data Engineers
• Visualization specialists
• Implement best practices in AI transformation, machine learning, and data-driven decision making
• 2.
• Develop analytical models to drive business efficiency and transformation
• Create advanced analytics models to deliver high-impact projects across multiple domains, including:
• **Customer & Growth Analytics**
• (customer segmentation, cohort analysis, churn, frequency, LTV, acquisition effectiveness)
• **Marketing Analytics & ROI Measurement**
• (campaign effectiveness, attribution, media ROI, performance tracking)
• **Personalization and Recommendation Engines**
• (menu layout and customization, customer journey personalization, CRM personalization etc.)
• **Sales Forecasting & Commercial Planning**
• (demand forecasting, store-level planning, budgeting and outlook support)
• **Pricing & Menu Analytics**
• (price elasticity, menu optimization, mix improvement, margin diagnostics, basket analysis)
• **Promotions & Campaign Analytics**
• (promo affinity modelling, uplift measurement, cannibalization analysis, offer effectiveness)
• **Labor, home delivery & transport optimization and scheduling models**
• (delivery time prediction, logistics efficiency, labor transport scheduling, labor productivity)
• **Store & Operations Analytics**
• (store performance diagnostics, productivity, cost optimization, efficiency levers)
• **Workforce Analytics**
• (employee performance analytics, attrition models)
• Ensure analytics outputs are
• decision-oriented
• , commercially relevant, and actionable.

2. Integrate Data Across Enterprise

• Oversee the creation of
• robust, scalable, and high-quality data foundations
• to enable analytics.
• Develop frameworks to
• integrate data across multiple systems
• – customer data platform, restaurant POS and operating systems, delivery logistics platforms, enterprise financial and sales reporting systems, HR and employee systems
• Own
• data sanity, metric definitions, and consistency
• across systems
• Ensure alignment and synchronization between source systems, data layers, and analytical outputs
• Manage the
• end-to-end customer data stack
• , ensuring usability for analytics and business teams

3. Embed Analytics into Decision Making

• Drive analytics and AI initiatives from problem definition to impact delivery:
• Partner with business stakeholders to identify
• high-value analytics and AI use cases
• Lead
• experimentation frameworks (A/B testing)
• .
• Promote a data-driven culture across markets and functions
• Lead project scoping, prioritization, and delivery governance
• Ensure models, insights, and tools are
• explainable, trusted, and adopted
• Track and articulate
• business impact and value realization

4. Establish Analytics Governance & Best Practices

• Act as a trusted analytics partner to senior stakeholders across Marketing, Commercial, Operations, Finance, and Digital:
• Define standards for Data modeling, Machine learning deployment, Experimentation, Analytics documentation
• Ensure compliance with data privacy and governance standards
• Partner with technology, data engineering, and IT teams to ensure sustainable data access and governance

5. Team Leadership & Capability Building

• Build and lead a high-performing analytics team:
• Manage, coach, and develop analytics talent across experience levels
• Foster a culture of curiosity, ownership, and continuous improvement
• Build future-ready capabilities across advanced analytics, forecasting, and AI

Education

• Bachelor’s or Master’s Degree in Engineering in Computer Science / Mathematics/ Statistics / Economics

Experience

• 10+ years of experience in analytics, data science, or related fields with exposure to stakeholder engagement and project management.

Technical Skills

• Strong foundation in
• statistics, predictive modeling, and machine learning
• .
• Strong exposure to
• F&B, QSR, retail, or consumer businesses
• preferred
• Hands-on experience with

Python, SQL

• , and data visualization tools (Tableau / Power BI).
• Experience with
• customer data platforms, experimentation frameworks, customer analytics techniques
• (LTV, cohort analysis, segmentation, churn modeling),
• marketing & pricing analytics frameworks
• and forecasting techniques.

Other Skills

• Strong business acumen with the ability to connect analytics to commercial outcomes.
• Excellent communication skills, able to present complex insights to non-technical audiences.
• Structured problem-solving mindset with strong prioritization skills.
• Strong grounding in statistics, forecasting, and applied analytics
• Excellent stakeholder management and communication skills