Multi-Disciplined Scientist III

Job Description

Duration: 12 months, possibility of extension

Pay: $63 hourly

• Develop and implement mathematical programming, simulation models, and cost models (e.g., linear and mixed-integer programming, discrete-event simulation) to address real-world business challenges.
• Analyze process flows, resource allocation, production planning, and logistics scenarios, recommending evidence-based improvements.
• Collect, clean, and analyze operational data; translate findings into model parameters and actionable insights.
• Collaborate with cross-functional teams to frame business problems, gather requirements, and 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.

• 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 (e.g., CPLEX, Gurobi, Pyomo + GLPK), simulation tools (e.g., Any Logic, Sim Py), and programming languages such as Python.
• Strong analytical and critical thinking skills with attention to detail and a 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.

• Master's degree preferred.
• Experience with data preparation, workflow automation, and visualization is a plus.
• Exposure to manufacturing, supply chain, or commercial analytics preferred.