Multi-Disciplined Scientist

Job Title: Multi-Disciplined Scientist III

Location: Painted Post, NY 14870

Summary Of Job

Responsible 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 Skills

• Bachelor’s degree in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative discipline
• 7+ years of practical experience applying operations research and industrial engineering techniques to solve business or engineering problems
• Proficiency with optimization solvers such as CPLEX, Gurobi, and Pyomo+GLPK
• Proficiency with simulation tools such as AnyLogic and SimPy
• Proficiency in programming languages such as Python
• Strong analytical and critical thinking skills
• Attention to detail and passion for problem-solving
• Ability to communicate complex technical concepts clearly to both technical and non-technical audiences
• Collaborative team player with strong interpersonal skills
• Curious, adaptable, and eager to continuously learn and apply new methods
• Results-oriented and proactive in driving projects to completion
• Ability to collect, clean, and analyze operational data
• Ability to translate findings into model parameters and actionable insights
• Ability to analyze process flows, resource allocation, production planning, and logistics scenarios
• Ability to document models, methodologies, and results
• Ability to assist in deploying optimization, simulation, and cost modeling tools into production using modern software and platforms

Nice-to-have Skills

• Master’s degree preferred
• Experience with data preparation, workflow automation, and visualization
• Exposure to manufacturing, supply chain, or commercial analytics preferred

Key Responsibilities And Duties

• Develop 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.