Python Data Science | Mid/Senior
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Compass UOL is a global firm and part of the AI Revolution Company, together transforming organizations using Artificial Intelligence, Generative AI, and other of today's most advanced technologies.
We equip our team with proprietary and external AI-driven tools to design and build digital-native platforms, integrating cutting-edge technologies and enabling companies to innovate, transform their businesses, and drive success in their markets.
To achieve this, we attract and develop the best talent, creating opportunities that enhance people's lives and highlight the positive impact of disruptive technologies.
We empower borderless talent and promote knowledge and opportunities in the latest market trends, driving significant personal and professional growth.
Join us and be part of the AI-driven revolution.
/n Sólida bagagem em Pesquisa Operacional: modelagem matemática, otimização de processos, formulação de funções-objetivo, restrições e definição de variáveis de decisão; Experiência comprovada com Programação Linear Inteira Mista (MILP); Vivência em estudos de viabilidade técnica/econômica e simulação/modelagem de cenários; Domínio de Python; Experiência com bibliotecas open source de otimização (Pyomo ou OR-Tools); Experiência na construção de APIs REST com FastAPI; Conhecimento em banco de dados relacional: SQL / PostgreSQL; Prática com controle de versão utilizando Git e GitHub; Experiência com testes unitários e foco em cobertura de testes e qualidade de software.
/n Desenvolver e implementar soluções de Pesquisa Operacional com foco em otimização matemática, especialmente Programação Linear Inteira Mista (MILP); Conduzir estudos de viabilidade técnica e econômica e modelagem de múltiplos cenários operacionais; Realizar análises de estequiometria de reação e cálculos de Valor Presente Líquido (VPL) com base em valor real; Construir, otimizar e integrar modelos em Python, utilizando bibliotecas como Pyomo ou OR-Tools; Garantir a confiabilidade, manutenibilidade e qualidade do código por meio de testes unitários, alta cobertura de testes e boas práticas de versionamento.
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