Senior Data Scientist - Portfolio

BEES; Campinas; Sur place; BRL 240 000 - 360 000; Plein temps

Avantages offerts par ce poste

Performance based bonus

Attendance Bonus

Casual office and dress code

Days off

Health, dental, and life insurance

Discounts on Ambev products

School materials assurance

Language and training platforms

Résumé du poste

BEES, AB InBev’s B2B platform, is seeking a data scientist to advance AI strategy across a broad set of business problems, including portfolio optimization, recommendations, personalization, forecasting, segmentation, and insights discovery.

You will design and deploy ML/DL models, build scalable data pipelines with PySpark on cloud platforms, and collaborate with data engineering, product management, and stakeholders to deliver end-to-end AI solutions that drive measurable impact.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science or related quantitative field.

Responsabilités

• Collaborate on design of complex analyses and develop and deploy ML/DL algorithms for portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insight discovery.

Connaissances

ML in production

Statistical modeling

Python

PySpark / Spark

Experimentation frameworks

Communication

CI/CD

Creative thinking

Explainability

Formation

Bachelor’s degree in Mathematics/Statistics/Engineering/CS

Master’s degree preferred

PhD a plus

Outils

Databricks

Azure

Spark

CI/CD tools

Description du poste

Join us to build the future of B2B commerce!

BEES is AB InBev’s B2B platform. Through our ecosystem, merchants and retailers across 30 countries can stock their businesses quickly, easily, and securely.At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow.

Every line of code and every partnership is built in service of a single mission: to make commerce better for retailers and sellers around the world. Here, your work is notjust important. It makes a difference!

About the role:

The Team: BEES is the team driving AI strategy at BEES by building end-to-end products to serve our teams, customers, and partners across the globe. The organization is a cross-functional blend of AI/ML teams from Applied Research and Machine Learning Engineering to Machine Learning Platform Product Management. Together, the team is responsible for building the tools and products needed to deliver world-class AI/ML capabilities

As a member of BEES Applied Science team, you will develop solutions for challenging business problems in areas such as portfolio optimization, recommendations, personalization, forecasting, segmentation, and insights discovery.

What you will do:

• Collaborate on the designof complex analysis of datasets and the development and deployment of advanced machine learning and deep learning algorithms for portfolio optimization, recommendations, personalization, promos, segmentation, imputation, and insight discovery. Ensure that solutions are robust, scalable, and aligned with business objectives while mentoring junior and mid-level data scientists.
• Actively stimulatethe machine learning and deep learning update on advancements, continuously incorporating cutting-edge techniques to solve complex business problems. Champion the adoption of frontier algorithms to drive innovation and technical excellence across the team’s initiatives.
• Architect and optimizelarge-scale data processing workflows on cloud platforms such as Azure, Databricks, and Spark, ensuring performance and scalability. Guide best practices in leveraging these platforms to accelerate delivery.
• Support the design and implementation ofreliable data pipelines and modeling workflows using Python and PySpark. Introduce automation and reusable components that enhance team productivity and reduce operational overhead.
• Engage proactivelywith cross-functional teams—including data engineering, product management, and business stakeholders—to translate business needs into technical requirements and deliver impactful, end-to-end solutions. Foster an agile mindset, driving rapid iteration and continuous improvement.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s preferred; PhD a plus.
• Demonstrated success applying machine learning and statistical modeling techniques in production environments to drive measurable business impact.
• Communication skills, with the ability to translate complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
• Experience or strong familiarity with experimentation frameworks, model validation, and rigorous evaluation, ideally in high-stakes decision systems.
• Proven ability to apply machine learning and statistical models in production, balancing accuracy, stability, explainability, and real-world constraints.
• Proficiency in Python for analysis, modeling, and production workflows; experience with distributed data processing (e.g., Spark / PySpark) is a plus.
• Experience with modern ML development practices, including version control, CI/CD, and reproducible research and modeling workflows.
• Strong proficiency using AI coding agents and developer tools in a controlled, thoughtful, and production-oriented way to accelerate development without compromising quality.
• Creative, curious, and independent thinker who challenges assumptions, proposes novel approaches, and reasons deeply about complex systems.
• Excellent communication skills, able to clearly explain complex models and results to both technical and non-technical audiences.

What We Offer:

• Performance based bonus*
• Attendance Bonus*
• Casual office and dress code
• Days off*
• Health, dental, and life insurance
• Discounts on Ambev products*
• School materials assurance
• Language and training platforms

Equal Opportunity & Aff...

ABI GrowthGroup is proud to be an Equal Opportunity and Aff... 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.