Data Product Manager - Machine Learning Platform at Anheuser Busch InBev Canada

Campinas, São Paulo, Brazil -

Full Time

Start Date

Immediate

Expiry Date

15 Feb, 26

Salary

0.0

Posted On

17 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Products, Machine Learning, AI Solutions, Communication Skills, Agile Methodologies, Python, Stakeholder Engagement, Technical Documentation, Model Lifecycle, ML Observability, Cross-Functional Teams, Business Needs Translation, Model Performance, User-Friendly Design, ML Workflows, Technical Requirements

Industry

Manufacturing

Description

Please note that this role works 100% 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. What you'll do: Drive Strategic Alignment Collaborate with the Machine Learning Platform Group Product Manager (GDPM) to define the vision, mission, roadmap, and KPIs for ML platform capabilities and services. Provide regular updates and insights on platform adoption, model lifecycle efficiency, and AI enablement metrics to the GDPM and Product Leadership. Plan and Prioritize Develop quarterly plans with ML engineers, MLOps, and technical leaders, balancing business-driven AI initiatives, technical improvements to the platform, and infrastructure evolution. Assess team capacity to ensure priorities are realistic and aligned with broader AI/ML strategy. Execute and Deliver Partner closely with engineering teams to execute the quarterly backlog, ensuring smooth delivery of ML platform features, such as model training workflows, deployment tooling, observability, and governance. Define epics and High-Level Requirements (HLRs), facilitating refinement sessions focused on ML workflows, model lifecycle needs, and platform capabilities. Lead Agile ceremonies (stand-ups, planning, reviews, retros). Track team performance metrics and provide sprint summary reports with particular attention to platform reliability, efficiency, and adoption. Engage Stakeholders Maintain strong communication with technical and business stakeholders—including Data Scientists, ML Engineers, MLOps, and product teams—through regular updates. Present upcoming quarterly plans, negotiate scope or trade-offs, and align expectations across AI/ML stakeholders. Translate business and data science needs into clear, actionable backlog items that support scalable, reliable, and user-friendly ML platform capabilities. What you'll need: Proven experience working with data products focused on machine learning platforms, including exposure to data science workflows, ML model lifecycle, or AI-driven solutions. Familiarity with the end-to-end process of training, deploying, and monitoring machine learning models. Ability to translate business needs into technical requirements for ML and AI products. Exceptional communication skills to bridge business, engineering, and data science stakeholders. Advanced English proficiency for effective collaboration with global teams. Willingness to work on site in Campinas. More about you: Experience in product management or data product management, ideally with ML/AI products. Hands-on experience creating epics, High-Level Requirements (HLRs), and technical documentation for ML platforms or tooling. Basic Python knowledge (e.g., for understanding notebooks, model pipelines, or small automations). Experience working in Agile environments with cross-functional teams (data scientists, MLOps, ML engineers, platform teams). Experience with ML observability, model performance dashboards, or AI product usability. What We Offer: Performance based bonus* Attendance Bonus* Private pension plan Meal Allowance Casual office and dress code Days off* Health, dental, and life insurance Medicines discounts WellHub partnership Childcare subsidies Discounts on Ambev products* Clube Ben partnership Scholarship* School materials assurance Language and training platforms Transport allowance *Rules applied Equal Opportunity & Affirmative Action: AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. The following fields are optional, but anticipate the information for your registration*. Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. For more information: www.abinbev.com

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Responsibilities

The Data Product Manager will drive strategic alignment by collaborating with the Machine Learning Platform Group Product Manager to define the vision and roadmap for ML platform capabilities. They will also execute and deliver by partnering with engineering teams to ensure the smooth delivery of ML platform features and track performance metrics.