Senior Data Scientist – BEES Logistics

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Join a dynamic data science team dedicated to creating intelligent logistics systems that enhance delivery operations on a global scale.

• Design, develop, and implement machine learning models and optimization solutions throughout the entire lifecycle—from research and experimentation to production—focusing on planning, forecasting, and operational decision-making.

• Utilize advanced methodologies such as statistical modeling, optimization, geospatial analytics, and forecasting to enhance the efficiency, reliability, and cost-effectiveness of delivery operations.

• Convert intricate real-world logistics challenges into scalable mathematical models and data-driven systems.

• Participate in experimentation and performance assessment through offline analysis and online testing, ensuring that solutions are robust, scalable, and aligned with operational objectives.

• Write production-quality code and develop reusable data and modeling pipelines that perform reliably at scale.

• Work closely with engineers, product managers, operations teams, and business stakeholders to deliver impactful solutions.

• Foster continuous improvement by investigating new methodologies in machine learning, optimization, and applied statistics, raising the technical standards across the organization.

⛳️ Requirements

• Strong foundation in mathematics, statistics, and problem-solving skills.

• Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; a Master’s degree is preferred; a PhD is an advantage.

• Demonstrated experience in applying machine learning, optimization, or advanced analytics to real-world challenges in production settings.

• Familiarity with complex systems that involve uncertainty, constraints, and large-scale data.

• Proficiency in Python for data analysis, modeling, and production workflows; experience with distributed processing (e.g., Spark / PySpark) is a plus.

• Knowledge in at least one of the following areas: optimization, forecasting, geospatial analytics, or large-scale operational systems.

• Experience with experimentation frameworks, model validation, and performance monitoring.

• Solid understanding of software engineering best practices, including version control, CI/CD, and reproducible workflows.

• Capability to navigate ambiguity, decompose complex problems, and deliver practical, high-impact solutions.

• Excellent communication skills, with the capacity to articulate technical concepts to both technical and non-technical audiences.

🏝️ Benefits

• 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