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WareBee

Careers · Open role

Data Scientist (Optimization Science)

Engineering · full-time · Cambridge · Tel Aviv · Remote · Posted 2026-07-04

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About the role

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