Job Title: Senior Optimization 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. Originally posted on Himalayas