We are one of the leading technology groups in Italy. We operate as a Business & Technology Accelerator for companies, financial institutions, and public sector organizations, supporting the evolution of their IT and digital strategies. Through an ecosystem of companies that share values, business strategies, and a common vision, we enable our clients to unlock the full potential of technology, amplifying its positive impact on both the economy and society.

What to expect

You will act as the "Quantitative Architect" for our client projects. Rather than acting as a narrow specialist, you will own the end-to-end mathematical lifecycle for operational challenges. You will use statistical ML to forecast realities (e.g., demand, lead times) and formal Operations Research (LP/MIP/Heuristics) to optimize the client's response. Because we serve multiple clients, a key part of your role will be abstracting your solutions into reusable, scalable code templates rather than starting from scratch every time.

What you will do

• Design both the predictive models (Time-Series, XGBoost) to forecast business conditions and the prescriptive models (Linear/Mixed-Integer Programming) to optimize decisions.

• Translate messy, nuanced business problems from different clients into formal equations and adaptable codebases, accommodating slight variations in constraints from project to project.

• You won't just write notebook prototypes. You will write clean, robust, and scalable Python code (Pyomo, Scikit-learn, Scipy) that can be integrated into broader software pipelines.

• Develop reusable analytical assets, algorithms, and digital twins that can be rapidly customized for new clients with similar use cases (e.g., adapting a vehicle routing template for a new logistics client).

• Act as the subject matter expert during client engagements, explaining complex mathematical concepts and the "why" behind the algorithms to non-technical stakeholders.

What we expect from you

• PhD (preferred) or Master’s in Operations Research, Applied Mathematics, Industrial Engineering, Statistics, or a closely related quantitative discipline.

• Proven expertise in both Machine Learning (specifically forecasting and time-series) and Mathematical Optimization (LP, MIP, Heuristics).

• You are a scientist who codes. Advanced proficiency in Python and experience with industrial solvers (Gurobi, CPLEX, OR-Tools) and ML libraries.

• The ability to abstract a specific client problem into a generalized mathematical model, recognizing patterns across different projects.

• Nice to have: Experience in MRO (Maintenance, Repair, and Operations), supply chain, logistics, or manufacturing domains; Familiarity with version control (Git) and software engineering best practices.