Python Data Science | Mid/Senior

Accountabilities: • Design, develop, and implement Operations Research solutions focused on mathematical optimization, particularly Mixed-Integer Linear Programming (MILP).

• Conduct technical and economic feasibility studies, evaluate alternative strategies, and model multiple operational scenarios to support informed business decisions.

• Perform reaction stoichiometry analyses and calculate Net Present Value (NPV) using real-value assumptions to assess project feasibility and economic outcomes.

• Build, optimize, and integrate mathematical optimization models in Python using open-source libraries such as Pyomo or OR-Tools.

• Develop and maintain RESTful APIs using FastAPI to make optimization capabilities accessible and integrate them into broader systems.

• Ensure code reliability, maintainability, and performance through unit testing, high test coverage, version control, and adherence to software development best practices.

• Collaborate with relevant stakeholders to translate complex operational requirements into robust, efficient, and scalable technical solutions.

Requirements:

• Strong experience in Operations Research, including mathematical modeling, process optimization, objective function formulation, constraint definition, and decision variable selection.

• Proven hands-on experience with Mixed-Integer Linear Programming (MILP) and mathematical optimization techniques.

• Experience conducting technical and economic feasibility studies, as well as simulation and operational scenario modeling.

• Advanced proficiency in Python, including the ability to develop clean, efficient, and maintainable code.

• Practical experience with open-source optimization libraries such as Pyomo or OR-Tools.

• Experience designing and developing REST APIs using FastAPI.

• Knowledge of relational databases, including SQL and PostgreSQL.

• Proficiency with version control tools, particularly Git and GitHub.

• Experience writing unit tests, maintaining high test coverage, and applying software quality assurance practices.

• Strong analytical and problem-solving skills, attention to detail, and the ability to translate complex business challenges into structured technical solutions.

• A collaborative mindset, clear communication skills, and a commitment to continuous learning and technical excellence.

Benefits:

• Meal and/or food allowance.

• Medical and dental insurance.

• Pet health insurance.

• Home office allowance for remote positions.

• Welcome kit during onboarding.

• Life insurance.

• Access to psychological and nutritional support through Zenklub.

• TotalPass wellness and fitness benefits.

• Continuous learning and certification programs with partners such as Adobe, Anthropic, AWS, Google, Microsoft, and Salesforce.

• Partnerships and discounts to support personal and professional development.

• Access to UOL content.

• Maternity welcome kit.

• Extended maternity and paternity leave.

• Employee referral program.

• Remote work model, offering flexibility and the opportunity to work from Brazil. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1