A warehouse is an optimisation problem in a trench coat. Layouts, slotting, labour shifts, pick paths, replenishment — the difference between a good answer and a great one moves real money for every operator WareBee serves. As Data Scientist (Optimization Science) you will reach for linear programming, mixed-integer programming, constraint satisfaction, heuristic search, and simulation, and pick the right one for the problem in front of you. WareBee runs on two engines: Physical AI — a living, spatial model of the warehouse floor, its racks, aisles, and movement — and Process AI, which learns how work actually flows through it. Your optimisation work sits on top of both. What you will do Sit with operators and the product team, understand the real constraints, and turn fuzzy operational pain into formal models Solve real instances — at production scale, with messy warehouse data, against deadlines that matter Build solvers and heuristics that ship, not papers that don’t Pair with engineers to embed solvers behind clean APIs and feedback loops Validate against the truth (operations on the ground), not just against the model What we are looking for Strong foundations in operations research, mathematical optimisation, or applied mathematics Production experience with at least one solver ecosystem and one general-purpose programming language Comfort with messy real data, partial information, and changing constraints Pragmatism about when an optimal solution is overkill and a heuristic ships Curiosity about the operational domain — logistics, supply chain, warehousing Hands-on warehouse, logistics, or supply-chain experience — you’ve seen how a real floor runs (a strong plus) What we offer Real operational problems with real money on the table A small senior team that respects the craft Hybrid in Cambridge, UK or Tel Aviv, Israel — or fully remote #J-18808-Ljbffr
Data Scientist (Optimization Science)
