Multi-Disciplined Scientist

Job Title: Multi-Disciplined Scientist IIILocation: Painted Post, NY 14870 Summary Of JobResponsible for developing and implementing mathematical programming, simulation models, and cost models to solve real-world business challenges. The role supports process analysis, production planning, logistics optimization, operational data analysis, and deployment of optimization and simulation tools into production environments. Must-have/Required SkillsBachelor’s degree in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative discipline7+ years of practical experience applying operations research and industrial engineering techniques to solve business or engineering problemsProficiency with optimization solvers such as CPLEX, Gurobi, and Pyomo+GLPKProficiency with simulation tools such as AnyLogic and SimPyProficiency in programming languages such as PythonStrong analytical and critical thinking skillsAttention to detail and passion for problem-solvingAbility to communicate complex technical concepts clearly to both technical and non-technical audiencesCollaborative team player with strong interpersonal skillsCurious, adaptable, and eager to continuously learn and apply new methodsResults-oriented and proactive in driving projects to completionAbility to collect, clean, and analyze operational dataAbility to translate findings into model parameters and actionable insightsAbility to analyze process flows, resource allocation, production planning, and logistics scenariosAbility to document models, methodologies, and resultsAbility to assist in deploying optimization, simulation, and cost modeling tools into production using modern software and platforms Nice-to-have SkillsMaster’s degree preferredExperience with data preparation, workflow automation, and visualizationExposure to manufacturing, supply chain, or commercial analytics preferred Key Responsibilities And DutiesDevelop and implement mathematical programming, simulation models, and cost models including linear and mixed-integer programming and discrete-event simulation.Analyze process flows, resource allocation, production planning, and logistics scenarios.Recommend evidence-based improvements to business and operational processes.Collect, clean, and analyze operational data.Translate analytical findings into model parameters and actionable insights.Collaborate with cross-functional teams to frame business problems and gather requirements.Present results to technical and non-technical audiences.Document models, methodologies, and results.Support knowledge sharing and team best practices.Assist in deploying optimization, simulation, and cost modeling tools into production using modern software and platforms.