Data Product Manager | Computer Vision & Machine Learning

Location: São Paulo (on-site) 

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. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. 

We are looking for Data Product Managers to join our Computer Vision team, playing a critical role at the intersection of business, data science, and engineering. You will own the strategy, execution, and adoption of AI-powered computer vision products used across global markets. 

This role requires strong product leadership, fluency in ML-driven products, and the ability to translate complex technical capabilities into business value for commercial and customer stakeholders. 

What you'll do:

Drive Strategic Alignment 

• Partner with global commercial stakeholders across LATAM, US, and Mexico to enable product understanding, drive adoption, and unlock new Computer Vision use cases.
• Act as a product evangelist—educating stakeholders on product capabilities, limitations, and roadmap.
• Provide regular updates to customers and internal stakeholders on product adoption, model performance, and business impact. 

 Plan & Prioritize 

• Own quarterly product planning in collaboration with Data Scientists, Data Analysts, Data Engineers, ML Engineers and software engineers.
• Balance business visibility, technical improvements, and infrastructure evolution when defining priorities.
• Continuously assess team capacity and delivery risk to ensure plans are realistic, achievable, and aligned with broader product and business strategy. 

Execute & Deliver