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Operations Research Engineer

Pubblicato il 27-09-2026 - Duferco in Milano

We are expanding Duferco’s Corporate Innovation Team: a fast-moving team operating in a startup-like environment, backed by the stability and scale of a globally diversified group.Si candidi (facendo clic sul pulsante apposito) dopo aver controllato tutte le informazioni di lavoro riportate di seguito.We are looking for an Operations Research Engineer: someone who works close to business teams, understands messy operational and planning problems, develops optimization models and algorithms to solve them efficiently, and turns solutions into practical tools used by a diverse range of stakeholders.You will work across domains such as energy, trading, logistics, steel, insurance, sports, and other sectors — not as an external consultant, but as part of the group itself, with the ownership and continuity of an internal product and engineering team.You will identify opportunities, prototype optimization-based tools, evaluate impact, and help deploy solutions that remove bottlenecks, improve decision-making, and create leverage across the business.About the TeamWe sit close to real business problems and have the freedom to prototype and ship quickly, with AI being already part of our daily workflow.We care about building solutions that work in the real world: useful tools, reliable and smart decisions, better workflows, and systems that create measurable impact.We appreciate people who enjoy ownership, fast iteration, pragmatic problem solving, and working directly with users to understand how things actually get done.What You’ll DoDesign, build, test,



and deploy optimization-based solutions for a variety of business applicationsCollaborate closely with business and technical teams to understand needs, formalize optimization problems, prototype solutions, measure impact, and iterate — not just execute predefined specsDevelop linear, nonlinear, and mixed-integer programming models, along with heuristic and stochastic optimization methods, to enhance operational efficiency and decision-makingEnsure the robustness, scalability, and interpretability of optimization solutions deployed in production environmentsResearch and evaluate emerging technologies and methodologies in operations research and mathematical optimization to drive innovation.What We OfferA high-autonomy role with direct influence on how optimization is applied across the groupReal business problems with visible impactModern AI-assisted tools and time to explore new technologies and approachesA fast-moving, collaborative environment with talented and ambitious peopleA broad variety of technical and business challenges across different domainsCompetitive compensation and benefitsFlexible working hours and hybrid work setup.You’re Probably a Fit IfYou have a master’s degree with at least 2-3 years of relevant experience,



or a Ph.D. in Operations Research, Applied Mathematics, Industrial Engineering, or a related field.You have in-depth knowledge of mathematical programming (linear, integer, etc.), various heuristic and metaheuristic approaches, and stochastic optimization methodsYou are proficient in optimization software (e.G., Gurobi, CPLEX, open solvers) and have strong programming skills in Python or other languages relevant to optimization and modelingYou have experience in building and solving large-scale optimization models and the ability to communicate insights and trade-offs clearly to stakeholdersYou enjoy working close to users and business teams, understanding how work happens, and turning messy problems into useful optimization-based solutionsYou have proven track record of implementing optimization-based solutions in real-world settings and/or in publishing optimization-based research in Operations Research related journalsYou are pragmatic about using AI in the daily workflow: excited by what it can do, but aware of its limitations, failure modes, and the importance of good evaluation.Experience with forecasting and machine learning, structured and unstructured data, simulation, database systems, AWS, deploying tools in production environments or complex operational domains is a plus.You do not need experience with every technology and optimization method. xysqume Curiosity, analytical thinking, adaptability, and the ability to turn optimization into practical business impact matter much more.#J-18808-Ljbffr

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