Senior Data Scientist | BEES Personalization

AB InBev Growth Group; Brasil; Teletrabalho; BRL 160.000 - 200.000; Tempo integral

Resumo da oferta

A leading beverage company in Brazil is seeking a Machine Learning Expert for their BEES Applied Science team. The role involves developing solutions for complex business challenges through machine learning and data analysis. The ideal candidate possesses strong knowledge in machine learning techniques, programming in Python/PySpark, and experience with cloud platforms like Azure and Databricks. The position offers a performance-based bonus and comprehensive insurance coverage.

Serviços

Performance based bonus

Attendance Bonus

Health, dental, and life insurance

Discounts on company products

Qualificações

• Strong mastery of machine and deep learning algorithms.
• Experience mentoring and coaching data scientists and engineers.
• Exceptional communication skills to convey complex concepts.

Responsabilidades

• Collaborate on complex analysis and development of machine learning algorithms.
• Stimulate updates in machine learning and deep learning advancements.
• Architect and optimize large-scale data processing workflows.

Conhecimentos

Machine Learning

Deep Learning

Python

Data Analysis

CI/CD

Formação académica

Bachelor’s degree in Computer Science, Engineering, Mathematics or related field

Master’s or PhD

Ferramentas

Azure

Databricks

Spark

Descrição da oferta de emprego

Remoto

About BEES

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 and the companies that service them, unlocking new growth opportunities for all. With offices in São Paulo and Campinas, we encourage our team to participate in major events and significant meetings throughout the year.

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, promos, segmentation, imputation, and insights discovery. The ideal candidate should hold a bachelor's degree in any quantitative field; strong mastery of frontier algorithms in machine and deep learning; plus working knowledge of cloud platforms (Azure, Databricks) for ML applications. Proficiency in python / pyspark programming, collaboration tools, and working knowledge of CI/CD tools like GitHub is required. Knowledge of workflows for automation is also required.

What you will do:

• Collaborate on the design of 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 stimulate the 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 optimize large-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 of reliable data pipelines and modeling workflows using Python and PySpark. Introduce automation and reusable components that enhance team productivity and reduce operational overhead.
• Engage proactively with 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 Computer Science, Engineering, Mathematics, or any quantitative field; Master’s or PhD strongly preferred.
• Demonstrated success applying machine learning and statistical modeling techniques in production environments to drive measurable business impact.
• Experience mentoring and coaching data scientists and engineers, fostering skill development and knowledge sharing within cross-functional teams.
• Experience working with cloud platforms such as Azure, Databricks, and Spark for big data processing and analysis.
• Exceptional communication skills, with the ability to translate complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
• Proficiency in Python/PySpark for data manipulation, analysis, and modeling tasks. Strong knowledge of relevant libraries and frameworks.
• Good knowledge of CI/CD tools like Github for version control and collaboration. Familiarity with other collaboration tools is a plus.
• Understanding of workflows and automation tools to streamline processes and enhance efficiency.

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 & 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.