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About Us: INSYLO is a pioneering AgTech startup that specializes in digital solutions for the animal farming and feed supply chain. Our mission is to revolutionize logistics in this sector through innovation and precision. We’re now embarking on an exciting project to develop a cutting-edge logistics optimization engine to streamline feed supply chain operations. To achieve this, we’re seeking a highly skilled and research-driven Operations Research Engineer to lead the development of this critical system and become a key player in our team. Role Overview: The Operations Research Engineer will design and implement state-of-the-art optimization algorithms to address logistical challenges in the animal feed supply chain. This is a hands-on role requiring strong expertise in research, mathematical modeling, and algorithm development , translating complex mathematical concepts (Routing, Inventory, Prediction) into a robust, scalable, and clean software product. Key Responsibilities: Algorithm and Model Development: Design and implement optimization algorithms for route planning, inventory management, and supply chain scheduling. Develop mathematical models to simulate and optimize logistics processes specific to the animal feed sector. Ensure solutions are scalable and adaptable to varying operational scenarios. Develop and use digital twins and simulations to evaluate, refine, and validate optimization models Integration and Collaboration: Work closely with our software development team to integrate algorithms into a functional optimization engine. Collaborate with the product team to ensure algorithms align with user needs and industry requirements. Data Analysis and Insights: Analyze operational data to identify inefficiencies and propose algorithmic solutions. Leverage machine learning or AI techniques where relevant to enhance optimization outcomes. Innovation and Research: Stay abreast of advancements in operations research, logistics, and supply chain optimization. Drive innovation by experimenting with new techniques and methodologies. Performance Evaluation and Iteration: Develop metrics to evaluate the effectiveness of algorithms. Continuously refine solutions based on performance results and real-world feedback. Qualifications and Experience: Master’s Degree (MSc) in Engineering, Applied Mathematics, Computer Science, or a related field. Proven expertise in developing optimization algorithms (e.g., heuristic methods, metaheuristics, genetic algorithms, etc.). Proven expertise with solvers like Gurobi, CPLEX, or Google OR-Tools. Strong programming skills in Python, with experience in optimization libraries and machine learning frameworks. Familiarity with logistics, supply chain management, or transport optimization is highly desirable. Solid understanding of data structures, algorithms, and computational complexity. Personal Attributes: Passionate about solving complex logistical challenges. Proactive and self-reliant, with a hands-on approach to problem-solving. Strong analytical and critical thinking skills. Collaborative and communicative, thriving in team-oriented environments. Fluent in English; additional language skills in Spanish/Catalan are a plus. Will Work With: Play a pivotal role as an integral member of our R&D Engineering team, contributing to innovative projects and driving technological advancements.
