Data Scientist - Operational & Optimisation-Focused AI
£700+ per day | Inside IR35 | Long-term programme (2-3 years)

I'm currently looking for Data Scientists to join a highly capable, collaborative team working on real operational problems at serious scale within a well‑established, commercially driven organisation.This is a role for someone who enjoys building things that actually run the business - not experiments that sit on a slide deck. You'll be working on postoptimization, decision‑making problems where the output of your models directly affects cost, performance, and customer outcomes every day.

Location & Contract

* Rate: £700+ per day (Inside IR35, depending on experience)
* Contract: Rolling 6‑month contracts, with a realistic 2-3 year roadmap of work
* Working pattern: Hybrid - 2-3 days per week onsite in West London / Paddington area and West Drayton
* Start: ASAP (subject to onboarding)

What the role is really about

In this role, you won't be siloed away from the business. You'll be embedded alongside engineers and operational stakeholders, working on problems where data science is central to how decisions are made, not just how performance is reported.You will:

* Design and build optimisation, predictive, and prescriptive models that support live operational decision‑making
* Work on problems where multiple constraints, trade‑offs, and dependencies matter (cost, service levels, experience, risk)
* Take solutions from idea → model → production, and stay involved once they're live
* Iterate based on real‑world performance and business feedback, not theoretical metrics
* Explain why a model behaves as it does and help the business trust and use it

A good way to think about this role: you are shaping the engine that runs day‑to‑day operations, not creating insights for someone else to interpret later.

I'm particularly keen to speak to you if your background includes:

* Hands‑on data science using Python, ML Frameworks and modern tooling
* Experience with optimisation, simulation, machine learning, or advanced analytics applied to real systems
* Clear examples of models you've personally built and put into production, not just prototyped
* Working with engineers to deploy, monitor, and improve solutions over time
* Operating in commercial, corporate environments where decisions have financial and operational consequences

Experience in supply chain, logistics, asset management, scheduling, or similar domains is useful - but what really matters is how you think about operational problems.

Why this role is worth a conversation

* The work is meaty, operational, and genuinely impactful
* You'll be surrounded by people who understand and value good data science
* There's long‑term stability (not a short "fire‑and‑forget" contract)
* You get to see your work run at scale, improve, and evolve

A quick but important note on CVs

This is a specialist role, and CVs that read as academic, R&D‑only, or proof‑of‑concept‑focused tend not to land well. Please make sure your CV clearly shows:

* What you personally built
* How it was used in production
* What measurable impact it had on the business

CVs that make that clear tend to stand out very quickly. If you enjoy solving hard, real‑world problems and want your models to matter, I think this is well worth exploring.If you'd like to talk it through, I'd be very happy to have a conversation.

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