Numerical Optimization Specialist Position Available In Steuben, New York

Numerical Optimization Specialist New York, Painted Post 06/12/2025 Contract Active

Job Description:

Job Summary
We are seeking an experienced Numerical Optimization Specialist to design, develop, and implement large-scale optimization models to solve complex industrial and manufacturing problems. This role bridges advanced mathematical modeling and real-world operations, supporting business objectives in areas such as scheduling, predictive control, and supply chain optimization. The ideal candidate is highly analytical, collaborative, and capable of translating business logic into scalable mathematical formulations. Key Responsibilities
Design and implement large-scale optimization models, including LP, NLP, and MILP.
Collaborate with cross-functional teams (supply chain, operations, engineering) to define optimization problems.
Formulate and enhance Model Predictive Control (MPC) frameworks.
Define and gather data requirements, working with data scientists and engineers to preprocess input data.
Build and refine optimization models using tools such as Gurobi, Pyomo, AMPL, and MATLAB.
Translate business workflows and processes into mathematical models and objective functions.
Leverage machine learning and data analysis techniques to inform model constraints and parameters.
Clearly communicate technical optimization results to both technical and non-technical stakeholders.
Document methodologies and provide training to internal stakeholders, including engineering and manufacturing teams.
Required Qualifications

Education:

Ph.D. in Chemical Engineering, Computer Science, Operations Research, Applied Mathematics, or a related field with a specialization in optimization.

Experience:

Minimum of 10 years in industrial roles focusing on numerical optimization.
Additional academic experience in numerical optimization is a plus.

Technical Skills:

Deep expertise in convex optimization, MILPs, NLPs, and solvers like Gurobi.
Proficient in Python (especially with Pyomo), MATLAB, and AMPL.
Familiarity with Git and version control systems.
Strong mathematical modeling skills with the ability to map business problems to quantitative frameworks.

Soft Skills:

Proven ability to work in interdisciplinary teams.
Effective communicator with both technical and business stakeholders.
Excellent problem-solving skills, teamwork, and adaptability. Preferred Qualifications
Familiarity with machine learning and data analytics to support optimization modeling.
Experience working with manufacturing, scheduling, or supply chain functions.
Background in translating business logic into structured optimization goals and constraints.
Exposure to additional modeling environments like GAMS or MiniZinc. Certifications (if any)
None required. Relevant certifications in optimization, data science, or applied mathematics are considered a plus.