Chapter Lead Data Analytics | Personalization

 

This is a on-site position, based in São Paulo (SP) OR Campinas (SP).

About us

AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.

About AB InBev Growth Group

Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.

In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft.

What you'll do:

Management routine

• Manage and lead a high-performance team of Data Analysts and Analytics Engineers (8 to 10 resources).
• Work with product leaders, engineering, and commercial strategy to form a unified data-driven strategy.
• Support analysis request prioritization with stakeholders and Data Product Managers (DPMs).
• Actively balance team leadership efforts with practical development/coding of data products, metrics, and visualizations to drive business.

Technical routine

• Review to verify that best practices have been followed for high-quality products, recommend appropriate data sources and models, ensuring scalability and high reuse.
• Drive the business strategy by providing insights into current performance and highlighting areas of opportunity for growth. To do this, conduct advanced data analysis, statistical modeling, and machine learning models to answer specific business questions, extract insights and predictive patterns from large datasets to explain and expose potential opportunities from the data.
• Develop data sets/schemas consuming data from multiple sources such as internal databases, analysis tools, unstructured sources, and other external sources.
• Demonstrate a solid understanding of complex data models, data structures, and best practices for data governance to support the data platform team in definitions and executions following best practices appropriate to use cases.

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