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