Responsibilities
- Build & Own Routing and Network Models: Design and implement routing models across transportation, warehousing, and resupply networks.
- Encode constraints related to: Distance and time, Asset and lane capacity, Availability, readiness, and risk.
- Support multi-hop, time-phased, and event-aware routing across dynamic networks.
- Algorithm Engineering & Optimization: Implement and tune routing solvers using exact, heuristic, and hybrid algorithms.
- Scale routing algorithms to large graphs, real-time updates, and uncertain inputs.
- Evaluate tradeoffs between solution quality, runtime, and operational robustness.
- Network Data Ownership: Own routing datasets including nodes, edges, costs, capacities, and constraints.
- Validate and maintain network representations used by all routing and planning systems.
- Handle data gaps, uncertainty, and changing network conditions without breaking execution.
- Production Integration: Integrate routing systems into real-time and batch planning pipelines.
- Partner with feasibility, simulation, and execution teams to validate route executability.
- Support scenario testing, what-if analysis, and iterative optimization based on real operational feedback.
Requirements
- Strong programming skills in Python or similar, with experience translating mathematical models into production-grade systems.
- Experience integrating routing or optimization algorithms into live planning pipelines with monitoring, validation, and performance tuning.
- Degree or equivalent experience in Operations Research, Applied Math, Industrial Engineering, Computer Science, or related field.
- Strong foundation in: Graph theory and network optimization, Shortest-path algorithms (Dijkstra, A*, Bellman-Ford), Network flow models (max flow, min cut, min-cost flow).
- Experience with VRP, capacitated routing, or routing with time windows.
- Experience with large-scale graphs, time-expanded networks, or multi-commodity flow models.
- Hands-on experience with modeling languages and solvers such as Pyomo, GAMS, AMPL, CPLEX, or Gurobi.
- Ability to reason about scale, uncertainty, and time-dependent systems.
- Comfort owning routing logic and data end-to-end.
- Strong performance, correctness, and reliability mindset in high-stakes environments.
Nice to Have
- Experience with vehicle routing or transportation systems.
- Experience working alongside simulation or digital-twin teams.
- Exposure to defense, government, or mission-critical logistics.
- Experience with ML models, experimentation (A/B testing), or causal inference.
- Experience in data operationalization and production analytics.
