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.
About BEES
At BEES, our ambition is – and always will be – to put customers at the heart of everything we do, making their lives easier and their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and medium-sized retailers, unlocking new growth opportunities for all.
The BEES AI organization drives data science and machine learning strategy across logistics, operations, and customer-facing products. We build end-to-end intelligent systems that optimize how goods move through our network, improving reliability, efficiency, and the overall customer experience at global scale.
As a member of the BEES Logistics Data Science team, you will develop data-driven solutions that power delivery planning, operational efficiency, and customer promise accuracy across multiple markets.
What you'll do:
- Be part of a high-impact data science team building intelligent logistics systems that optimize delivery operations at a global scale.
- Design, develop, and deploy machine learning models and optimization solutions across the full lifecycle — from research and experimentation to production — focusing on planning, forecasting, and operational decision-making.
- Apply advanced techniques such as statistical modeling, optimization, geospatial analytics, and forecasting to improve efficiency, reliability, and cost of delivery operations.
- Translate complex real-world logistics constraints into scalable mathematical models and data-driven systems.
- Contribute to experimentation and performance evaluation through offline analysis and online testing, ensuring solutions are robust, scalable, and aligned with operational goals.
- Write production-grade code and build reusable data and modeling pipelines that operate reliably at scale.
- Collaborate closely with engineers, product managers, operations teams, and business stakeholders to deliver impactful solutions.
- Drive continuous improvement by exploring new methodologies in machine learning, optimization, and applied statistics, raising the technical bar across the organization.
What you'll need:
- Strong foundation in mathematics, statistics, and problem solving.
- Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s preferred; PhD is a plus.
- Proven experience applying machine learning, optimization, or advanced analytics to real-world problems in production environments.
- Experience with complex systems involving uncertainty, constraints, and large-scale data.
- Proficiency in Python for data analysis, modeling, and production workflows; experience with distributed processing (e.g., Spark / PySpark) is a plus.
- Familiarity with at least one of the following domains: optimization, forecasting, geospatial analytics, or large-scale operational systems.
- Experience with experimentation frameworks, model validation, and performance monitoring.
- Strong understanding of software engineering best practices, including version control, CI/CD, and reproducible workflows.
- Ability to work with ambiguity, break down complex problems, and deliver practical, high-impact solutions.
- Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
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
Skills Required
- Strong foundation in mathematics, statistics, and problem solving
- Bachelor's degree in Mathematics, Statistics, Engineering, Computer Science, or related quantitative field
- Master's degree
- PhD
- Proven experience applying machine learning, optimization, or advanced analytics to production problems
- Experience with complex systems involving uncertainty, constraints, and large-scale data
- Proficiency in Python for data analysis, modeling, and production workflows
- Experience with distributed processing (e.g., Spark / PySpark)
- Familiarity with at least one domain: optimization, forecasting, geospatial analytics, or large-scale operational systems
- Experience with experimentation frameworks, model validation, and performance monitoring
- Strong understanding of software engineering best practices including version control, CI/CD, and reproducible workflows
- Ability to work with ambiguity and deliver practical, high-impact solutions
- Excellent communication skills for technical and non-technical audiences
What We Do
We are the world’s leading brewer bringing people together for a better world. For centuries, the experience of sharing a beer has brought people and cultures together. Even in our hyper-connected, always-on world, this simple act is as meaningful today as it was generations ago. We are AB InBev. Committed to driving growth that leads to better living for more people in more places. Through brands and experiences that bring people together. Through our dedication to brewing the best beer with the best ingredients. And through our commitment to helping farmers, retailers, entrepreneurs, and communities grow. We are building a company to last. Not just for a decade. But for the next 100 years. Through our brands and our investment in communities, we will bring more people together, making our company an integral part of our consumers’ lives for generations to come. Our diverse portfolio of well over 500 beer brands includes global brands Budweiser, Corona and Stella Artois; multi-country brands Beck’s, Castle, Castle Light, Leffe and Hoegaarden; and local champions such as Aguila, Antarctica, Bud Light, Brahma, Cass, Chernigivske, Cristal, Harbin, Jupiler, Klinskoye, Michelob Ultra, Modelo Especial, Quilmes, Victoria, Sedrin, Sibirskaya Korona, and Skol. Anheuser-Busch InBev is a publicly traded company (Euronext: ABI) based in Leuven, Belgium, with secondary listings on the Mexico (MEXBOL: ANB) and South Africa (JSE: ANH) stock exchanges and with American Depositary Receipts on the New York Stock Exchange (NYSE: BUD).
