Operations Research Lead - Data Scientist

Harnham; Greater London; Hybrid; GBP 110,700 - 166,050; Full time

Job summary

A major international transport company is seeking a Senior Operations Research Data Scientist for a contract role focused on optimising logistics and operational efficiency. This hands-on position requires proven experience in building optimisation solutions in production. The candidate will work closely with teams to deliver practical models for operational problems. The role offers £600-£900 per day, a hybrid work environment in London, and involves occasional travel within Europe.

Qualifications

• Proven experience building optimisation or simulation solutions in production.
• Strong operations research or mathematical optimisation background.
• Experience working on logistics or supply chain optimisation problems.

Responsibilities

• Deliver real optimisation solutions for large-scale operations.
• Work on logistics, resource allocation, and supply chain optimisation.
• Translate operational problems into practical optimisation approaches.

Skills

Operations Research

Supply Chain Optimization

Logistics Optimization

Mathematical Optimization

Simulation Modeling

Python

Job description

Senior Operations Research Data Scientist Contract | £600-£900/day | Hybrid London

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.

Key requirements:

• Proven experience building optimisation or simulation solutions in production
• Strong operations research or mathematical optimisation background
• Experience working on logistics or supply‑chain optimisation problems
• Experience translating business problems into optimisation models
• Strong Python‑based modelling experience
• Ability to work closely with operational stakeholders

Typical backgrounds include airlines, logistics platforms, retail supply chain, transport networks or other large operational environments.

Contract details:

• £600‑£900 per day
• Initial contract to end of year with likely extension
• Hybrid working – 3 days onsite in London
• Occasional travel within Europe may be required

To apply, please email …

Desired Skills and Experience

• Operations Research
• Supply Chain Optimization
• Logistics Optimization
• Mathematical Optimization
• Simulation Modeling
• Vehicle Routing
• Mixed Integer Programming
• Decision Science
• Python
• Optimization Algorithms