Why This Role Stands Out
This hybrid role offers an exciting opportunity to develop cutting-edge AI-driven decision-support systems, enhancing your skills in machine learning and optimization while contributing to significant improvements in operational performance. You'll thrive here if you have a strong quantitative background and a passion for solving complex transportation and logistics challenges with data-driven solutions.
Quick Overview
Job Description
We are seeking an Operations Research Scientist to develop AI-driven decision-support systems that improve operational performance, network efficiency, service reliability, and cost optimization.
This role combines Artificial Intelligence, Machine Learning, Reinforcement Learning, and Mathematical Optimization to solve complex transportation and logistics challenges. The ideal candidate will build scalable models and intelligent systems that support real-time and strategic decision-making.
Key Responsibilities
- Develop machine learning, reinforcement learning, and optimization models to solve complex operational challenges.
- Design predictive and prescriptive analytics solutions that improve efficiency, resiliency, and business performance.
- Build decision-support systems for scheduling, routing, resource allocation, and network recovery.
- Apply optimization techniques including LP, MIP, and nonlinear optimization.
- Analyze large datasets to identify operational improvements and cost-saving opportunities.
- Partner with business and technology teams to deploy AI and analytical solutions into production environments.
- Support and enhance existing AI, optimization, and decision-support applications.
- Communicate analytical findings and recommendations to business leaders and stakeholders.
Required Qualifications
- Master's or PhD in Operations Research, Industrial Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related quantitative field.
- 3+ years of experience developing AI, machine learning, optimization, or decision-support solutions.
- Experience with predictive analytics, machine learning, reinforcement learning, and optimization modeling.
- Strong Python programming skills.
- Experience with SQL and large-scale datasets.
- Experience deploying analytical models into production environments.
Preferred Qualifications
- Experience with Gurobi, CPLEX, or other optimization solvers.
- Transportation, logistics, supply chain, or network optimization experience.
- Experience with scheduling, routing, capacity planning, or operational recovery.
- Experience building real-time analytics and intelligent decision-support systems.
Technical Skills
- Python
- SQL
- Machine Learning
- Reinforcement Learning
- Optimization (LP, MIP, NLP)
- Predictive & Prescriptive Analytics
- Gurobi / CPLEX
- Java or C++ (preferred)
Impact
This role will help drive AI-powered decision-making, improve network performance, increase operational resiliency, reduce costs, and deliver measurable business value through advanced analytics and intelligent automation.
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