Operations Research Analyst

Role Description The Operations Research Analyst applies advanced analytical, mathematical, and statistical methods to help organizations solve complex problems, improve decision-making, and enhance operational efficiency. This role focuses on using data-driven modeling and optimization techniques to analyze processes, forecast outcomes, and recommend strategic improvements that drive performance across business functions. The analyst transforms data into actionable insights, enabling management teams to make informed, evidence-based decisions in areas such as logistics, production, resource allocation, finance, and strategy.Key responsibilities include gathering and interpreting data from multiple sources, developing mathematical models, and applying simulation, optimization, and predictive analytics to evaluate alternative solutions. The Operations Research Analyst collaborates with cross-functional teams to understand operational challenges, define performance metrics, and design solutions that improve cost-effectiveness, productivity, and overall system performance. They present findings through detailed reports, dashboards, and visualizations, making complex quantitative results accessible to decision-makers.The role also involves evaluating existing workflows, identifying inefficiencies, and recommending process enhancements supported by empirical analysis. The analyst uses tools such as statistical software, machine learning algorithms, and optimization platforms to support initiatives in supply chain management, scheduling, pricing strategy, and capacity planning. By integrating data analytics with strategic insight, the Operations Research Analyst plays a vital role in bridging technical modeling with real-world business applications.This position offers the opportunity to contribute directly to organizational success through analytical innovation and process optimization. It is ideal for individuals who enjoy problem-solving, quantitative reasoning, and applying advanced analytics to create measurable business impact.QualificationsBachelor’s degree in operations research, applied mathematics, industrial engineering, computer science, economics, or a related field.Strong proficiency in mathematical modeling, optimization techniques, and statistical analysis.Experience with data analysis tools and programming languages such as Python, R, MATLAB, or SQL.Familiarity with operations research tools such as Gurobi, CPLEX, or Excel Solver.Understanding of linear and nonlinear programming, simulation, forecasting, and decision analysis.Strong analytical and critical-thinking skills with the ability to translate complex models into practical recommendations.Excellent communication and presentation abilities for conveying technical results to non-technical audiences.Attention to detail, problem-solving mindset, and ability to manage multiple analytical projects simultaneously.Knowledge of data visualization and reporting tools such as Tableau or Power BI.Commitment to continuous learning in quantitative methods, optimization, and data science applications.