Optimisation AI Scientist
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About this role
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:
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Formulate supply chain optimisation problems as rigorous mathematical models - objective functions, costs, penalties, and constraints
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Configure and run optimisation models for customer pilots and implementation, and support Solutions Architects in delivering results and debriefs
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Build and run Python models against third-party solvers across multiple dataset scales, and benchmark results across use cases
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Work with Engineering and Data Science leads to define the path to production-grade solver integration and customer specific implementations within Pigment's architecture
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Engage technically with solver vendor teams during partnership evaluation
Who you are and what you can do:
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Demonstrable experience formulating and solving optimisation problems for real-world operational use cases
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Proficiency in Python with hands-on experience in a major solver library (Gurobi, OR-Tools, CPLEX, HiGHS, or equivalent)
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Experience with supply chain/operations data — SKUs, BOMs, capacity constraints, service levels, lead times, inventory targets etc.
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Understanding of core OR techniques: branch-and-bound, LP relaxation, constraint programming, sensitivity analysis
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Degree in Operations Research, Applied Mathematics, Industrial Engineering, CS, or related field (MS/PhD advantageous)
Company
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