![]() A research analyst is typically very quantitative, analytical, logical, and good at managing numbers and data. ![]() These data-driven insights are typically applied according to process management and process improvement frameworks such as Six Sigma and Lean, which strive to reduce variation and eliminate waste in operations. A research analyst is responsible for researching, analyzing, interpreting, and presenting data related to markets, operations, finance/accounting, economics, customers, and other information related to the field they work in. Monte Carlo simulations and other probabilistic analyses may also be used to discover areas of sensitivity and risk. Operational data is input into programs such as Microsoft Excel and Solver, R, and Python, where mathematical optimization techniques such as linear programming (LP) are applied to find the best solution for business problems. The tools of operations research are similar to those of other fields relying heavily on quantitative analysis and statistics. The ability to harness vast amounts of data on day-to-day operations has created opportunities to rigorously optimize processes for cost, quality control, inventory management, and other goals, making operations research an important part of many businesses. Operations research is the use of statistical analysis and mathematical optimization techniques to help organizations solve problems and improve decision-making.
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