Alexandre Romeo

Introduction

I don't learn supply chain from textbooks — I've lived it for 25 years, from the warehouse floor to the executive boardroom. My career spans the full chain: 10 years in logistics operations (warehouse, transport, physical flows), 10 years in production scheduling and procurement (order management, supplier coordination), and 5 years combining supply chain expertise with data science and mathematical optimization. What this means in practice: I eliminate the most expensive cost in Data/AI projects — the knowledge transfer gap between domain experts and technical teams. I am both. My strongest proof: I designed and operated a parametric cost model for pharmaceutical packaging — 500+ references across 5 production sites, 87 chained calculations with binary decision variables, used for multi-million euro tenders. I was the central coordinator across 11 sites, leading executive board meetings to drive pricing and production decisions. The title was 'Business Analyst'. The actual role was pricing and tender orchestration across the entire value chain. I've since formalized these skills in Python: MILP optimization with PuLP (Big M technique), demand forecasting benchmarks (12 models on 179 products — feature-engineered ML outperformed pure time series models), retail analytics identifying €3.1M in revenue opportunities, a full SCM optimization module based on Chopra's framework, and an interactive S&OP prototype integrating 5 modules (demand planning, production, stocks, HR, finance) with a built-in allocation optimizer. Technical stack: Python, PuLP/MILP, Polars, scikit-learn, XGBoost, Optuna, Prophet, NeuralForecast, SQL, Git. Learning: Julia/JuMP. I'm looking for roles where supply chain depth and technical optimization intersect — not to do research, but to optimize cash and flows. Supply Chain Data Scientist, Optimization Specialist, Demand Planning Analyst, S&OP Lead.

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