The Senior Manager / Associate Director, Commercial & Marketing Analytics, will be a highly strategic and influential leader responsible for driving profitable growth across our diverse CPG portfolio. This role demands a proven expert with 12+ years of experience, possessing deep specialization in Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), Revenue Growth Management (RGM), Consumer Analytics, and Route-to-Market (RTM) optimization.

The successful candidate will leverage advanced data analytics, statistical modeling, and AI/ML techniques to transform complex data into actionable commercial and marketing strategies, significantly influencing brand investment, pricing, promotions, assortment, trade spend, and sales force effectiveness to achieve market leadership and financial targets.

Key Responsibilities:

1. Marketing Effectiveness & Media Mix Optimization:

- Marketing Mix Modeling (MMM): Lead the design, implementation, and interpretation of advanced MMM analyses to quantify the ROI of marketing investments (e.g., traditional advertising, digital media, sponsorships, experiential marketing) across brands and channels.

- Multi-Touch Attribution (MTA): Develop and implement MTA models to understand the incremental impact of individual marketing touchpoints on consumer conversion pathways, particularly for digital channels.

- Budget Optimization: Provide data-driven recommendations for optimal allocation of marketing budgets across various media channels, campaigns, and brands to maximize incremental sales and brand equity.

- Performance Monitoring: Establish and monitor key marketing effectiveness KPIs, identify trends, and provide proactive insights to Marketing leadership.

- Brand Health & Equity: Analyze the impact of marketing activities on brand health metrics (awareness, consideration, preference) and connect these to sales performance.

2. Revenue Growth Management (RGM) Leadership & Optimization:

- Strategy & Frameworks: Lead the development and continuous refinement of the company's RGM analytics framework, encompassing pricing, promotions, assortment, trade terms, and pack/price architecture.

- Pricing & Pack/Price Architecture: Conduct deep analysis of price elasticity, competitive dynamics, and consumer value perception to recommend optimal pricing strategies and pack configurations that balance volume, revenue, and margin across all channels.

- Trade Promotion Optimization (TPO): Design, execute, and meticulously analyze promotional effectiveness (ROI, lift, cannibalization) across various channels (on-premise, off-premise, e-commerce). Leverage AI/ML to build predictive models for promotion effectiveness and optimize trade spend allocation.

- Assortment Optimization: Analyze consumer purchasing behavior, channel dynamics, and profitability to recommend optimal product assortment strategies by channel, region, and customer segment.

3. Advanced Consumer Analytics & Insights:

- Consumer Behavior & Segmentation: Utilize advanced analytical techniques (e.g., clustering, predictive modeling, lifetime value analysis) on vast consumer data sets (POS, loyalty, panel, digital engagement, first-party data) to identify key consumer segments, understand their purchase drivers, occasions, and preferences.

- Demand Forecasting: Significantly enhance the accuracy of demand forecasting models by integrating comprehensive consumer insights, promotional plans, external market data (e.g., weather, events, social sentiment), and advanced AI/ML techniques.

- Innovation & White Space Identification: Identify emerging consumer trends, unmet needs, and market white spaces to inform new product development, portfolio expansion, and targeted marketing campaigns.

4. Route-to-Market (RTM) Strategy & Effectiveness:

- Channel & Customer Segmentation: Conduct in-depth analysis of performance across different RTM channels (e.g., wholesale, direct, e-commerce, distributor networks) and customer segments (e.g., large chains, independent stores, bars) to identify optimization opportunities and efficiency gains.

- Sales Force Effectiveness: Develop sophisticated analytics to assess sales territory performance, optimize call planning, identify coaching opportunities, measure the impact of sales initiatives, and inform resource allocation.

- Distributor & Partner Performance: Provide data-driven insights to improve distributor performance, optimize inventory flow through the distribution network, and enhance collaborative planning with third-party partners.

- Digital RTM & E-commerce: Analyze e-commerce performance, direct-to-consumer (D2C) channels, and last-mile delivery data to enhance digital presence, conversion funnels, and fulfillment strategies.

5. Data & Technology Enablement & AI/ML Leadership:

- Data Strategy & Governance: Champion enterprise-wide data quality, integrity, and accessibility. Partner with IT, Data Engineering, and Data Science teams to integrate disparate data sources (internal sales, syndicated data, loyalty, digital media logs, MMM inputs) into a unified and scalable analytical platform.

- Tool & Platform Expertise: Expertly utilize and recommend advanced analytics tools, visualization platforms (e.g., Tableau, Power BI), statistical software (e.g., Python, R), and potentially specialized marketing effectiveness or RGM/TPM platforms.

- AI/ML Application & Innovation: Drive the identification, prototyping, and implementation of cutting-edge AI/ML models for advanced forecasting, optimization, personalization, anomaly detection, and potentially generative AI applications in content or insights generation.

- Data Storytelling & Visualization: Master the art of translating complex analytical findings into clear, concise, and compelling narratives and visualizations that effectively influence senior leadership, cross-functional teams, and external partners.

6. Leadership, Collaboration & Mentorship:

- Strategic Influence: Act as a primary thought leader and trusted advisor to senior leadership in Sales, Marketing, Finance, and IT, shaping commercial and marketing strategies through data-driven insights.

- Cross-Functional Collaboration: Foster strong, collaborative relationships with diverse stakeholders across all commercial functions to ensure analytical insights are integrated into strategic planning and operational execution.

- Team Development: Mentor, coach, and develop junior analysts and data scientists, fostering a culture of continuous learning, analytical rigor, innovation, and business impact.

- Project Management: Lead and manage complex analytical projects from conceptualization through deployment, ensuring timely delivery, adherence to scope, and measurable business impact.

Qualifications:

Education: Bachelor's degree in a highly quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Engineering, Business Analytics). Master's degree (MBA or MS in a quantitative field) highly preferred.

Experience: 12+ years of progressive experience in data analytics, business intelligence, or data science roles, with at least 5-7 years specifically within the CPG (Consumer Packaged Goods) industry. Significant exposure to Alcobev specifically preferred.

Mandatory Deep Expertise:

- Marketing Mix Modeling (MMM) and/or Multi-Touch Attribution (MTA).

- Revenue Growth Management (RGM) methodologies and execution.

- Advanced Consumer Analytics (segmentation, predictive modeling).

- Route-to-Market (RTM) optimization and sales force effectiveness.

Domain Knowledge:

- Profound understanding of CPG commercial levers across both on-premise and off-premise channels.

- Expertise in leveraging syndicated data sources (e.g., NielsenIQ, Circana, Numerator, Kantar) and integrating them with internal data.

- Strong grasp of omnichannel consumer behavior and digital marketing landscapes.

Technical Proficiency:

- Expert-level SQL proficiency for complex data extraction, transformation, and analysis.

- Advanced programming skills in Python or R for statistical modeling, machine learning, and data manipulation.

- Mastery of data visualization tools (e.g., Tableau, Power BI, Looker) for dashboard development and compelling storytelling.

- Hands-on experience with cloud data platforms (e.g., AWS, Azure, GCP) and related services (e.g., Data Lakes, Data Warehouses, ML services).

- Experience with big data technologies (e.g., Spark) is a significant plus.

- Analytical & Problem-Solving: Exceptional analytical, quantitative, and critical thinking skills, with a proven ability to frame complex business problems into solvable analytical challenges and translate findings into practical, impactful business strategies.

- Communication & Influence: Superior written and verbal communication skills, including the ability to simplify complex technical concepts for non-technical audiences and influence decision-making at all levels, including executive leadership.

- Leadership & Collaboration: Demonstrated ability to lead complex analytical initiatives, manage cross-functional projects, build consensus, and effectively mentor and develop analytical talent.

- Business Acumen: Deep understanding of CPG business models, value chains, market dynamics, competitive landscapes, and regulatory environments (especially relevant for Alcobev).

- Adaptability: Proven ability to thrive in a fast-paced, highly ambiguous, and dynamic environment with evolving business priorities.

Preferred Qualifications:

- Prior experience in a leading management consulting firm (e.g., McKinsey, BCG,Bain, Accenture Strategy) with a focus on CPG or Retail analytics.

- Specific experience with marketing automation platforms (e.g., Salesforce Marketing Cloud, Adobe Experience Cloud).

- Familiarity with specific RGM/TPM/MTA software solutions (e.g., Aera Technology, Anaplan, Nielsen Unified Marketing Measurement).

- Experience in applying advanced AI/ML techniques beyond traditional regression, including deep learning, NLP, or generative AI for marketing/commercial applications.