Senior OR Analyst

UPS Supply Chain Solutions•US - IS MARYLAND (MDROA), MD

2d•$114,024 - $212,844

About The Position

The Senior Operations Research (OR) Analyst leads the design, development, and deployment of optimization solutions for UPS's final-mile delivery operations. This role applies mathematical programming, heuristic and metaheuristic algorithms, machine learning, and high-performance computing to some of the largest and most complex routing and dispatching problems in the logistics industry and turns them into production systems that deliver measurable operational impact. Working closely with business stakeholders, software engineers, data scientists, and data engineers, you will own the full solution lifecycle: problem formulation, model and algorithm design, validation, deployment, performance tuning, and continuous improvement.

Requirements

Ph.D. required in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Civil Engineering, Data Science, or a closely related quantitative field.
Experience designing, developing, and implementing moderately to highly complex optimization models and algorithms, including leading initiatives from problem definition through deployment.
Strong knowledge of Operations Research methods, including linear and mixed-integer programming, network optimization, heuristic and metaheuristic techniques, and vehicle routing or related combinatorial optimization problems.
Hands-on experience with optimization solvers such as Gurobi, CPLEX, Xpress, or OR-Tools.
Strong programming skills in Python, Java, C++, or similar languages, and proficiency in SQL, with experience writing clean, maintainable code.
Strong written and verbal communication skills, including the ability to explain complex technical concepts and recommendations to both technical and business audiences.
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 solving large-scale transportation and logistics problems such as vehicle routing with time windows (VRPTW), pickup-and-delivery, dynamic routing, territory optimization, and final-mile delivery.
Experience with advanced optimization methods such as column generation, branch-and-price, Benders decomposition, Lagrangian relaxation, or dynamic programming.
Experience with high-performance, parallel, distributed, cloud, or GPU computing, and with performance engineering for large-scale optimization systems.
Experience integrating optimization models with applications, APIs, databases, and cloud platforms in enterprise decision-support systems.
Experience applying machine learning, predictive analytics, simulation, or geospatial analytics alongside optimization.

Responsibilities

Lead the design, development, and continuous improvement of final-mile routing, dispatch, and resource allocation solutions, combining exact methods, heuristics, metaheuristics, and decomposition approaches to produce high-quality solutions within operational time limits.
Translate operational requirements into mathematical models using linear and mixed-integer programming, network optimization, stochastic optimization, and related methods.
Engineer solutions for scale, using parallel and distributed computing and performance profiling to improve runtime and solution quality for large, real-world problem instances.
Validate and monitor models through benchmarking, sensitivity and scenario analysis, and production performance tracking to ensure robustness and business alignment.
Partner with software and data engineering teams to deploy solutions into enterprise systems, applying machine learning and data science techniques where they strengthen optimization outcomes.