Senior Data Scientist - Bees Logistics

Jobgether SRL; Brasil; Presencial; BRL 260 000 - 420 000; Tempo integral

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Resumo da oferta

Jobgether, representando BEES Logistics no Brasil, procura um Senior Data Scientist para liderar projetos de ML, otimização e analytics avançado em rede logística global. Você trabalhará com forecasting, geospatial analytics e deployment de modelos em produção.

A posição envolve interação com equipes de engenharia, produto e operações, com forte foco em entregar melhorias de confiabilidade, eficiência e custo, impactando diretamente a experiência do cliente em escala.

Qualificações

• Mestrado ou PhD em área quantitativa é desejável.
• Experiência comprovada em ML, otimização ou analytics avançado em produção.
• Forte em Python para análise de dados, modelagem e workflows de produção.
• Experiência com sistemas de grande escala envolvendo incerteza e dados volumosos.
• Conhecimento em pelo menos um dos domínios: otimização, forecasting, geospatial analytics ou sistemas operacionais.
• Experiência com frameworks de experimentação, validação de modelos e monitoramento de desempenho.
• Boas práticas de engenharia de software, controle de versões e reprodutibilidade.
• Conhecimento de Spark/PySpark é um diferencial.

Responsabilidades

• Desenhar, desenvolver e implantar modelos de ML e soluções de otimização para melhorar planejamento logístico.
• Traduzir restrições logísticas complexas em modelos matemáticos e dados.
• Construir pipelines de dados em produção e estruturas reutilizáveis de modelagem.
• Aplicar forecasting, otimização e geospatial analytics para melhorar desempenho de entrega.
• Conduzir experimentação, avaliação offline e testes online para validar impacto de modelos.
• Colaborar com engenheiros, product managers e operations para soluções de data science.
• Contribuir para melhoria contínua com novas metodologias de ML e estatística aplicada.

Conhecimentos

Python

Machine learning

Optimization

Forecasting

Geospatial analytics

Experimentation

Spark/PySpark

Comunicação

Problema-solving

Formação académica

Master’s degree or PhD

Ferramentas

Spark/PySpark

Descrição da oferta de emprego

Senior Data Scientist - BEES Logistics

Empresa : Jobgether
Tipo de Emprego : Periodo Integral
Brazil
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Descrição do Emprego - Senior Data Scientist - BEES Logistics

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.