Data Scientist; Optimization Science

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 Ware Bee 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.

Ware Bee 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.

• 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

• 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)

• 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