Senior Operations Research Scientist

About the role

As a Senior Operations Research Scientist you will design and implement optimisation systems that balance supply and demand across a large‑scale logistics network. You will work with massive geospatial and real‑time data sets to create automated decision‑making tools that run in a dynamic, production environment.

Key responsibilities

• Develop high‑performance optimisation models using mixed‑integer programming, constraint programming, stochastic programming and meta‑heuristics.
• Translate models into production‑ready code, integrate them with CI/CD pipelines and Docker containers, and monitor their performance at scale.
• Collaborate with engineering teams to ensure clean, maintainable, type‑safe Python code and robust testing practices.
• Guide junior scientists, conduct historical benchmarking, and manage the full lifecycle of models in live operations.
• Analyse trace data to generate hypotheses, test ideas, and propose business‑impacting improvements.

Required profile

• Extensive experience designing large‑scale scheduling, rostering or shift‑planning optimisation systems in production.
• Deep knowledge of exact optimisation techniques such as mixed‑integer programming, decomposition and capacity planning.
• Proven ability to apply meta‑heuristic methods when exact approaches hit scaling limits.
• Strong understanding of software development best practices, including testing, version control and containerisation.
• Experience in logistics or last‑mile delivery is highly beneficial.

Required skills

• Python (object‑oriented, type‑safe)
• Pyomo, PuLP
• SCIP, Gurobi
• Mixed‑integer programming (MIP)
• Meta‑heuristics, constraint programming, stochastic programming
• Docker
• CI/CD pipelines
• Git