Senior Operations Research Lead: Final-Mile Optimization

GSV UPS General Services; Maryland; On-site; USD 114,000 - 213,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

401(k) retirement plan

Paid holidays and personal time

Paid sick leave

Job summary

UPS is seeking a Senior Operations Research Analyst to design, develop, and deploy optimization solutions for final-mile routing and dispatch. You will own the full solution lifecycle from problem formulation to deployment and continuous improvement, collaborating with software and data teams to scale models across enterprise systems.

The role requires a Ph.D. in a quantitative field, expert knowledge of MILP, network optimization, and parallel computing, and strong programming skills in

Qualifications

• Ph.D. required in a quantitative field.
• Experience designing, developing, and deploying optimization models and algorithms.
• Strong knowledge of OR methods including MILP, network optimization, heuristics, and routing.

Responsibilities

• Lead the design, development, and continuous improvement of final-mile routing and resource allocation solutions.
• Translate operational requirements into mathematical models using linear and mixed-integer programming.
• Engineer scalable solutions using parallel/distributed computing and performance profiling.
• Validate models through benchmarking, sensitivity analysis, and production performance tracking.
• Collaborate with software and data engineering teams to deploy solutions into enterprise systems.

Skills

OR methods

Programming: Python/Java/C++

Communication skills

Education

Ph.D. in Operations Research or related field

Tools

Gurobi

CPLEX

Xpress

OR-Tools

Job description

UPS is seeking a Senior Operations Research Analyst to design, develop, and deploy optimization solutions for final-mile routing and dispatch. You will own the full solution lifecycle from problem formulation to deployment and continuous improvement, collaborating with software and data teams to scale models across enterprise systems.

The role requires a Ph.D. in a quantitative field, expert knowledge of MILP, network optimization, and parallel computing, and strong programming skills in