Data Scientist

Lorien

London,

£73,917 per year - estimated ?

Contract

Data Scientist – Optimisation & Applied Analytics

Contract duration: 6months (12months of work road mapped)

Day rate: 800 Inside IR35

Location/Hybrid: 2-3 days per week to Heathrow Airport

A major global airline, undergoing a multi‑million‑pound data and optimisation transformation, is looking for a Data Scientist to join their high‑performing Decision Support & Optimisation function.

This role is end‑to‑end, hands‑on, and deeply embedded in the business. You’ll work at the start of new product builds, shaping and delivering AI‑powered optimisation tools that keep people and aircraft moving efficiently in one of the most operationally complex industries in the world.

What You’ll Do

• Build and deploy applied statistics, machine learning and optimisation models that support mission‑critical operational decisions. • Work closely with data engineers, understanding their workflows and collaborating to take models from ideation all the way into production environments. • Craft and define optimisation problems from scratch: decision spaces, constraints, objective functions. • Use strong data visualisation and communication skills to influence stakeholders at all levels. • Partner with operational teams to embed tools directly into workflows and measure real‑world impact. • Own delivery end‑to‑end with far better working hours than typical consulting—while still delivering meaningful change.

What We’re Looking For

Technical Expertise

• Degree or Master’s in Maths, Statistics, Data Science, Operational Research, or similar fields. • Strong applied statistics background. • Experience working with messy or complex datasets • Hands‑on exposure to integer programming, MIP, MILP, and applied optimisation. • Experience with optimisation tools such as CPLEX, MATLAB, OR‑Tools, or similar. • Some exposure to machine learning methods. • Ability to build and industrialise Python‑based data products. • Exceptional communication and storytelling abilities—able to interrogate both data and stakeholders. • Ability to articulate trade‑offs, design decisions and model assumptions clearly to non‑technical audiences.