Routes, assignments, inventories and shifts are math problems before they are software problems. In Labs you formulate them, choose the method and measure whether it truly improves on what the client already does. The role
- Formulate operational problems as optimization.
- Solve them with classical methods and compare them with quantum ones.
- Design how an improvement and its uncertainty are measured.
- Write down what worked, what didn't and why. Your first 90 days
- Day 30 You learn the Labs experiments and reproduce one.
- Day 60 You formulate a real client problem.
- Day 90 You present a measured improvement with its uncertainty. Stack and tools Python Optimization solvers NumPy / SciPy What we look for Must have




- An applied mathematics or actuarial science degree, finished or nearly finished.
- You code in Python.
- Rigor and honesty with results.
- You explain a model without hiding behind the formalism. Nice to have
- Operations research.
- Bayesian statistics. What working here is like What you build goes into products that operate real organizations. You work directly with the founders, with no layers between your code and production, under the same rule we give the intelligence: a person signs what is critical.

📌 Applied Mathematics (Lagos de Moreno)
🏢 Nuvnext
📍 Lagos de Moreno