Senior OR Analyst

UPS Supply Chain Solutions

About The Position

The Senior Operations Research (OR) Analyst designs, develops, and leads the deployment of advanced optimization, mathematical programming, and analytics-driven decision support systems across the organization. This role is responsible for formulating, implementing, and scaling complex quantitative models and algorithms, including linear, integer, mixed-integer, and network optimization methods, to enable data-driven planning, resource optimization, operational efficiency, and strategic decision support. The Senior OR Analyst owns the design, development, deployment, and continuous improvement of production-grade analytical solutions that drive cost optimization, network design, resource allocation, capacity planning, and operational performance across UPS. This position serves as a key technical leader responsible for solution architecture, model design, computational performance, and long-term sustainability of analytical products. The role requires close collaboration with business stakeholders, software engineers, data scientists, and data engineering teams to translate complex operational challenges into robust, scalable analytical solutions. The Senior OR Analyst provides leadership throughout the full lifecycle of analytical products, including requirements gathering, mathematical formulation, model development, validation, deployment, monitoring, performance tuning, and continuous improvement. This position also drives the adoption of Operations Research methodologies, establishes modeling best practices, and contributes to the strategic direction of analytical capabilities within the organization.

Requirements

Ph.D. REQUIRED in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Analytics, Data Science, or a closely related quantitative field.
Experience designing, developing, and implementing moderately to highly complex mathematical optimization models and analytical solutions.
Strong knowledge of operations research methodologies, including linear programming, mixed-integer programming, network optimization, and related techniques.
Experience with commercial optimization solvers such as Gurobi, CPLEX, Xpress, or equivalent technologies.
Strong programming skills and experience developing production-quality analytical software using languages such as Java, Python, C++, or similar.
Experience designing scalable, maintainable, and well-documented analytical solutions deployed in production environments.
Ability to independently solve complex technical problems and lead analytical initiatives from concept through deployment.
Strong written and verbal communication skills with the ability to engage both technical and business stakeholders.
Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

Nice To Haves

Experience with advanced decomposition and solution methodologies, including: Column Generation, Benders Decomposition, Lagrangian Relaxation, Dynamic Programming, Branch-and-Price, Metaheuristics and Hybrid Optimization Approaches
Experience developing optimization solutions deployed at enterprise scale.
Experience integrating optimization models with enterprise systems, APIs, databases, and data pipelines.
Experience supporting transportation, logistics, network design, supply chain optimization, or large-scale operational planning applications.
Experience applying AI and machine learning techniques alongside optimization and simulation methodologies.

Responsibilities

Lead the design, development, implementation, and deployment of advanced optimization, and decision support systems that address complex business and operational challenges.
Translate business requirements into quantitative modeling frameworks, including the definition of objectives, constraints, assumptions, performance measures, and solution methodologies.
Design and architect scalable optimization solutions that operate within enterprise production environments.
Develop mathematical models using operations research techniques, including linear programming, mixed-integer programming, network optimization, stochastic optimization, and related methodologies.
Evaluate and apply advanced solution approaches, decomposition techniques, heuristics, and algorithmic strategies to improve computational performance and solution quality.
Lead model validation, calibration, sensitivity analysis, scenario analysis, and stress testing efforts to ensure solution robustness and business alignment.
Collaborate with software engineering and data engineering teams to integrate optimization models into enterprise applications, cloud platforms, APIs, and automated decision-making workflows.
Monitor production performance and proactively identify opportunities for model enhancement, refactoring, automation, and operational improvements.
Establish and maintain comprehensive technical documentation, including model specifications, solution methodologies, assumptions, system architecture, and deployment procedures.
Communicate complex analytical concepts and results to technical and non-technical audiences, providing actionable insights and business recommendations.
Provide technical leadership and mentorship to Operations Research Analysts and other team members, supporting knowledge sharing and professional development.
Stay current with advances in operations research and related analytical disciplines, and drive their adoption where appropriate.
Lead or support multiple analytical initiatives simultaneously while ensuring alignment with business priorities and strategic objectives.