Back to jobs
New

Senior Data Scientist - Optimization

Campinas, Brazil

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 the Role 

The Senior Data Scientist – Optimization will be responsible for developing solutions at the intersection of Machine Learning and Advanced Optimization, with a focus on multi-objective, lexicographic, and evolutionary methods. This role will tackle strategic challenges related to delivery optimization, freight rate modeling, and minimum order value determination, integrating demand forecasting and large-scale operational constraints. 

This person will lead the design and implementation of mixed-integer optimization algorithms ensuring that solutions are scalable, interpretable, and directly impact key business metrics. 

We’re looking for someone with a strong mathematical background, scientific curiosity, collaborative mindset, and the ability to translate complex problems into quantitative solutions that balance cost, performance, and operational efficiency. 

What you'll do:

  • Implement and adapt PaCo (Pareto Ant Colony Optimization) algorithms for integer and mixed-variable optimization problems, addressing multiple objectives and business constraints.
  • Develop and benchmark models based on NSGA-II/III, MOEA/D, Simulated Annealing, CP-SAT, and Mixed-Integer Linear Programming (MILP)
  • Formulate composite objective functions and lexicographic hierarchies to prioritize goals such as logistics cost, service level, and profit margin.
  • Generate short- and mid-term demand forecasts using Machine Learning techniques (regression, ensembles, neural networks, time series) and integrate these forecasts as inputs to optimization models.
  • Build automated pipelines for training, inference, and optimization, ensuring traceability, versioning, and performance using Python, PySpark, MLflow, Docker, and GitHub Actions.
  • Execute and monitor experiments in cloud-based distributed environments (Azure, Databricks), optimizing both computational performance and cost.
  • Collaborate with Engineering, Product, and Operations teams to align business criteria, validate results, and ensure the impact of deployed solutions.

What you'll need:

  • Bachelor’s degree in engineering, Computer Science, Mathematics, Statistics, Operations Research, or related fields. A master’s or PhD in a relevant area is a plus.
  • Experience with multi-objective and lexicographic optimization (PaCo, NSGA-II/III, MOEA/D).
  • Familiarity with optimization frameworks such as Pyomo, OR-Tools, PuLP, PyMoo, Gurobi, or CPLEX.
  • Proficiency in Python and PySpark, with solid use of scientific libraries (NumPy, Pandas, SciPy, Scikit-learn).
  • Experience integrating ML models with optimization workflows (e.g., using forecasts as parameters in decision models).
  • Advanced English for working in a global environment.
  • Excellent analytical skills, clear communication, and a focus on impactful results. 

Nice to Have 

  • Experience with route optimization, supply chain, dynamic pricing, or last-mile logistics.
  • Knowledge of hybrid ML + OR methods (e.g., learning to estimate optimization parameters).
  • Experience with Azure Databricks, MLflow, Ray, Airflow, or other distributed computing platforms.
  • Publications, patents, or open-source contributions in multi-objective optimization. 

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 

 

Apply for this job

*

indicates a required field

Resume/CV*

Accepted file types: pdf, doc, docx, txt, rtf

Select...
Select...
Select...
Select...

Demographic Brazil

ABInBev is committed to creating a diverse and inclusive workforce and culture. We conduct confidential surveys to better understand & ensure we provide equal opportunity throughout our end-to-end recruitment process. Individuals seeking employment at ABInBev are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

When you apply to a job on this site, the personal information contained in your application will be collected by ABINBEV SERVICES LLC. Your personal information will be processed in accordance with the law for the purposes of managing ABINBEV’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results thereto, and as is otherwise needed in the recruitment and hiring processes.

On a voluntarily basis and subject to receiving your express consent, you’ll be asked demographic questions about your ethnicity, gender, sexual orientation and ability status. We collect this information for the purposes of supporting a diverse and inclusive workforce - it will not be considered in the hiring process or thereafter and all information will be reviewed collectively rather than individually. We won’t sell or share this information with third parties, but please note that we use Greenhouse Software Inc to manage the recruitment and hiring process on our behalf.

Your personal information will be retained by us for 2 (two) years from collection. You have the right to request access to your personal information, to request that your personal information be rectified or erased, and to request that processing of your personal data be restricted at any time. You can do so by contacting https://contactus.ab-inbev.com/ if you are located outside Europe, and emailing abi-team@firstprivacy.com if you are located in Europe. We expect that our procedures will deal fairly and promptly with your request. However, if you remain dissatisfied, you have the right to lodge a complaint with your local data protection authority.

Select...
Select...
Select...
Select...
Select...