Optimisation AI Scientist

Pigment is 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.

Responsibilities

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

Requirements

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

Nice to have

MS/PhD in Operations Research, Applied Mathematics, Industrial Engineering, CS, or related field (advantageous)