You will lead production scheduling automation and optimization project
+ Mathematical Modelling: You will develop mathematical models and algorithms to solve optimization problems. Formulate problems as linear programming, integer programming, mixed-integer programming, or constraint programming models. + Data Analysis: You will work with large datasets, conduct exploratory data analysis, and apply statistical and machine learning techniques to extract valuable insights. Identify patterns and trends in the data that can be used to improve optimization models and algorithms. + Model Implementation: You will implement mathematical models and algorithms using programming languages such as Python. Develop efficient and scalable code to solve complex optimization problems. + Simulation: You will develop and run simulation models to evaluate different scheduling strategies and their impact on manufacturing efficiency + Performance Evaluation:...