Python Data Science | Mid/Senior

Develop and implement Operations Research solutions focusing on mathematical optimization, especially Mixed Integer Linear Programming (MILP); Conduct technical and economic feasibility studies and model multiple operational scenarios; Perform reaction stoichiometry analyses and Net Present Value (NPV) calculations based on real value; Build, optimize, and integrate models in Python using libraries such as Pyomo or OR-Tools; Ensure code reliability, maintainability, and quality through unit testing, high test coverage, and good version control practices. Solid background in Operations Research: mathematical modeling, process optimization, objective function formulation, constraints, and decision variable definition; Proven experience with Mixed Integer Linear Programming (MILP); Experience with technical/economic feasibility studies and scenario simulation/modeling; Mastery of Python; Experience with open-source optimization libraries (Pyomo or OR-Tools); Experience building REST APIs with FastAPI; Knowledge of relational databases: SQL / PostgreSQL; Practice with version control using Git and GitHub; Experience with unit tests and a focus on test coverage and software quality. Additional Information Benefits: Meal vouchers and/or food vouchers; Health and dental insurance; Pet health insurance; Home office allowance (for remote positions); Welcome kit upon onboarding.