Optimisation AI Scientist
We are hiring an Optimisation AI Scientist to own the technical delivery of Pigment's solver pilot programme and build the foundations of a production-grade optimisation capability - moving customers from descriptive planning to prescriptive, solver-driven decision-making.
This role is partially customer-facing: leading and shaping the formulation of each client's optimisation problem, directly involved in implementations.
What you will do:
Formulate supply chain optimisation problems as rigorous mathematical models - objective functions, costs, penalties, and constraints
Configure and run optimisation models for customer pilots and implementation, and support Solutions Architects in delivering results and debriefs
Build and run Python models against third-party solvers across multiple dataset scales, and benchmark results across use cases
Work with Engineering and Data Science leads to define the path to production-grade solver integration and customer specific implementations within Pigment's architecture
Engage technically with solver vendor teams during partnership evaluation
Who you are and what you can do:
Demonstrable experience formulating and solving optimisation problems for real-world operational use cases
Proficiency in Python with hands-on experience in a major solver library (Gurobi, OR-Tools, CPLEX, HiGHS, or equivalent)
Experience with supply chain/operations data - SKUs, BOMs, capacity constraints, service levels, lead times, inventory targets etc.
Understanding of core OR techniques: branch-and-bound, LP relaxation, constraint programming, sensitivity analysis
Degree in Operations Research, Applied Mathematics, Industrial Engineering, CS, or related field (MS/PhD advantageous)