AB InBev | Growth Group - Senior Data Scientist - Portfolio
Requirements
• 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.
Responsibilities
• 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. • Collaborate on the design • 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. • Actively stimulate • 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. • Architect and optimize • 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. • Support the design and implementation of • 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. • Engage proactively
Benefits
• Performance based bonus* • Attendance Bonus* • Private pension plan • Casual office and dress code • Health, dental, and life insurance • Medicines discounts • WellHub partnership • Childcare subsidies • Discounts on Ambev products* • Clube Ben partnership • School materials assurance • Language and training platforms • Transport allowance • Equal Opportunity & Affirmative Action:
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