This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist - BEES Logistics based in Brazil.
This role sits at the core of a global digital transformation initiative, focused on building intelligent systems that redefine how products move through complex logistics networks. You will join a high-impact data science environment where machine learning, optimization, and advanced analytics are applied to solve large-scale operational challenges across multiple markets. The position plays a key role in improving delivery reliability, efficiency, and cost-effectiveness, directly influencing customer experience at scale. You will work on end-to-end solutions, from research and modeling to production deployment, within a highly collaborative and data-driven organization. The role requires strong problem-solving skills and the ability to translate real-world logistics constraints into scalable algorithms. It offers exposure to cutting-edge techniques in forecasting, geospatial analytics, and optimization, with significant ownership and visibility. You will collaborate closely with engineering, product, and operations teams in a fast-paced, innovation-oriented environment.
Accountabilities:
- Design, develop, and deploy machine learning models and optimization solutions to improve logistics planning, forecasting, and operational decision-making.
- Translate complex logistics constraints into scalable mathematical, statistical, and data-driven models.
- Build production-ready data pipelines and reusable modeling frameworks to support large-scale deployment.
- Apply advanced techniques such as forecasting, optimization, and geospatial analytics to improve delivery performance and efficiency.
- Conduct experimentation, offline evaluation, and online testing to validate model performance and business impact.
- Collaborate with engineers, product managers, and operations teams to deliver end-to-end data science solutions.
- Contribute to continuous improvement by exploring and applying new methodologies in machine learning and applied statistics.
Requirements:
- Strong foundation in mathematics, statistics, computer science, or related quantitative fields (Master’s or PhD preferred).
- Proven experience applying machine learning, optimization, or advanced analytics in production environments.
- Strong Python programming skills for data analysis, modeling, and production workflows.
- Experience with large-scale or complex systems involving uncertainty, constraints, and high-volume data.
- Familiarity with at least one core domain: optimization, forecasting, geospatial analytics, or operational systems.
- Experience with experimentation frameworks, model validation, and performance monitoring.
- Strong understanding of software engineering best practices, including version control and reproducible workflows.
- Experience with distributed data processing tools (e.g., Spark/PySpark) is a plus.
- Strong analytical thinking, autonomy, and ability to work with ambiguity.
- Excellent communication skills, with the ability to explain technical concepts to diverse audiences.
Benefits:
- Performance-based bonus and attendance bonus (based on eligibility rules).
- Health, dental, and life insurance coverage.
- Private pension plan with employer contribution.
- Meal allowance and transport allowance.
- ️ WellHub partnership for fitness and wellness support.
- Childcare subsidies and family support programs.
- Access to scholarships, training platforms, and language learning resources.
- Discounts on company products and partner benefits programs.
- Casual office environment with flexible dress code.
- ️ Paid days off and additional leave benefits (based on policy rules).
- Medicine discounts and additional employee assistance programs.
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