Senior Operational Research

Job Title: Senior Operational Reseach Scientist Location: Remote – Latin America Preferred Type of Contract: Full-Time | Remote Salary Range: Market Rates Language Requirements: Professional English (written and verbal) Our client is seeking a skilled Senior Operational Research Scientist with deep expertise in optimization modeling and production-grade decision-support systems to join their growing team. You will play a key role in designing, deploying, and scaling advanced optimization solutions that solve complex business challenges while partnering with cross-functional stakeholders to drive measurable business outcomes. Your work will directly impact operational efficiency, strategic decision-making, and long-term business growth. Key Responsibilities Design, develop, and optimize advanced Operations Research models using Linear Programming (LP), Mixed Integer Programming (MIP), heuristics, metaheuristics, decomposition techniques, and stochastic or robust optimization methods. Lead the architecture and implementation of scalable optimization pipelines, ensuring maintainability, performance, and seamless integration with enterprise applications. Collaborate with business stakeholders to translate operational challenges, constraints, and objectives into optimization models and measurable KPIs. Identify technical bottlenecks and organizational process improvements, recommending practical optimization strategies that maximize business value and ROI. Mentor junior Operations Research Scientists through technical reviews, coaching, and knowledge sharing while promoting engineering best practices. Drive technical roadmap planning, technology evaluation, and solution design, balancing long-term architecture with short-term business priorities. Establish model validation, monitoring, data governance, and quality assurance processes to ensure reliable, transparent, and production-ready optimization solutions. Must-Have Qualifications MS or PhD in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or a related quantitative field. 5+ years of professional experience designing, deploying, and maintaining Operations Research solutions in production environments. Deep expertise in optimization techniques including heuristics, metaheuristics, Benders Decomposition, Column Generation, Lagrangian Relaxation, and hybrid optimization approaches. Strong programming skills in Python or C++ with hands-on experience using optimization tools such as Gurobi, CPLEX, and Pyomo. Experience integrating optimization models with enterprise systems, APIs, distributed computing environments, and modern data engineering pipelines. Proven ability to deliver optimization solutions with measurable improvements in operational efficiency, service levels, revenue, or cost reduction. Excellent communication skills with the ability to explain assumptions, trade-offs, and technical concepts to both technical and non-technical stakeholders while leading cross-functional initiatives. Preferred Qualifications Experience delivering optimization solutions across multiple industries and business domains. Background in building scalable, cloud-based optimization platforms and production ML/OR pipelines. Experience defining optimization strategy and influencing technical roadmaps within growing organizations. Passion for mentoring technical teams and fostering a collaborative engineering culture. Strong business acumen with a practical, ROI-focused approach to solving complex operational problems.