Senior Data Scientist - BEES Logistics

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 p