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Data Product Manager | Computer Vision & Machine Learning
Позиция в одной из крупнейших FMCG-компаний мира с возможностью работать над передовыми AI-решениями. Отличный социальный пакет и масштабные задачи компенсируют отсутствие удаленного формата работы.
Сложность вакансии
Роль требует глубокого понимания жизненного цикла ML и опыта управления сложными техническими продуктами в глобальном масштабе. Высокая планка обусловлена необходимостью взаимодействия с международными стейкхолдерами на английском и испанском языках.
Анализ зарплаты
Предлагаемая позиция в Сан-Паулу соответствует уровню Senior/Lead Product Manager в международной компании. Рыночные оценки для таких ролей в Бразилии варьируются в зависимости от опыта работы с AI/ML, который высоко ценится.
Сопроводительное письмо
I am writing to express my strong interest in the Data Product Manager position within the Computer Vision team at AB InBev Growth Group. With a solid background in managing machine learning products and a deep understanding of the ML lifecycle—from data preparation to model monitoring—I am confident in my ability to bridge the gap between complex technical capabilities and tangible business value for your global markets.
In my previous experience, I have successfully led cross-functional teams of data scientists and engineers to deliver scalable AI solutions. I excel at translating business needs into technical requirements and am particularly skilled at creating clear documentation and high-level requirements. My fluency in English and Spanish, combined with my passion for driving digital transformation, aligns perfectly with the collaborative and international nature of the Growth Group.
I am eager to bring my expertise in product strategy and execution to AB InBev, helping to scale Computer Vision use cases across LATAM and beyond. Thank you for considering my application.
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Описание вакансии
**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
- Partner closely with engineering and data teams to execute the quarterly backlog and deliver high-impact Computer Vision capabilities.
- Drive delivery of:
New Computer Vision use cases
Scalable and secure APIs
State-of-the-art ML models
Comprehensive BI visualization.
- Define Epics and High-Level Requirements (HLRs), leading refinement sessions with a strong focus on:
Dashboard visibility
User experience (UX)
Model behavior and performance
- Lead Agile ceremonies, including daily stand-ups, sprint planning, reviews, and retrospectives.
- Track delivery and performance metrics, producing sprint summary reports with emphasis on:
Team productivity
Model metrics
Usage and adoption trends
Engage Stakeholders
- Maintain strong relationships with technical, commercial, and senior leadership stakeholders.
- Present quarterly roadmaps and progress updates with clarity and confidence.
- Proactively manage expectations by negotiating scope, timelines, and trade-offs across internal teams and customers.
What you'll need:
- Proven experience managing data or ML-driven products, ideally within Data Science Products.
- Strong understanding of the ML lifecycle, including data preparation, training, deployment, monitoring, and iteration.
- Ability to translate business problems into technical product requirements for ML and AI solutions.
- Exceptional written and verbal communication skills, capable of bridging business, engineering, and data science audiences.
- Fluent English and Advanced Spanish to collaborate effectively with global teams.
- Willingness to work on-site in São Paulo
More about you:
- Solid background in Product Management or Data Product Management, preferably with ML/AI products.
- Hands-on experience writing Epics, High-Level Requirements (HLRs), and technical documentation—documentation is one of your strengths.
- Foundational understanding of software architecture, including databases, APIs, and ML models.
- Experience working in Agile environments with highly cross-functional teams (Data Science, ML Engineering, MLOps, Backend, Frontend).
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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Навыки
- Product Management
- Machine Learning
- Computer Vision
- Data Science
- Agile
- API
- Business Intelligence
- Spanish
- English
- MLOps
Возможные вопросы на собеседовании
Проверка понимания специфики продукта и умения объяснять сложные вещи простыми словами.
Как бы вы объяснили ограничения технологии компьютерного зрения нетехническому бизнес-заказчику?
Оценка навыков приоритизации в условиях ограниченных ресурсов.
Как вы балансируете между внедрением новых фич и необходимостью улучшения технической инфраструктуры или производительности моделей?
Проверка опыта работы с метриками эффективности ML-продуктов.
Какие ключевые метрики (KPI) вы бы использовали для оценки успеха продукта на базе Computer Vision после его внедрения?
Оценка навыков управления ожиданиями в крупной корпорации.
Опишите ситуацию, когда вам пришлось отказать влиятельному стейкхолдеру в реализации его запроса. Как вы аргументировали свое решение?
Проверка технической грамотности в области жизненного цикла моделей.
Расскажите о вашем опыте работы с MLOps: как вы обеспечиваете мониторинг и своевременное обновление моделей в продакшене?
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