Company: Harnham
Location: London
Posted: April 17th, 2026
We are working with a major international transport and operations organisation building out a central AI and Data Science capability focused on solving complex operational optimisation problems across multiple business units.
This is a hands‑on contract role focused on delivering real optimisation solutions that directly impact large‑scale operations. The work centres around logistics, resource allocation and supply‑chain optimisation problems where the goal is to improve operational efficiency and reduce disruption across a distributed operational network.
Typical problem areas include optimisation of resource allocation, logistics planning and operational decision‑making. One example use case involves optimising the allocation of critical components across a large operational fleet to minimise downtime and maximise utilisation. Similar optimisation challenges exist across supply‑chain planning, operational efficiency and network optimisation.
The team operates centrally but works closely with operational stakeholders across the organisation. Contractors will typically take ownership of optimisation problems end‑to‑end, from understanding the business problem through to designing and delivering production‑ready optimisation models.
This role requires someone who has built optimisation or simulation solutions in real production environments. They are not looking for purely analytical data scientists or academic optimisation specialists. The successful candidate will be able to translate real‑world operational problems into practical optimisation approaches and deliver working solutions.
The role requires a consultative mindset and strong stakeholder engagement. You will be expected to work closely with business teams, identify optimisation opportunities and make clear technical recommendations.
Typical backgrounds include airlines, logistics platforms, retail supply chain, transport networks or other large operational environments.
To apply, please email …