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Hamilton Barnes 🌳

Head of Data Science

London
£100k – £120k/yr
Posted about 17 hours ago
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Principle AI Data Scientist (LLM Architecture)

A leading UK Managed Service Provider is launching a new applied AI practice for enterprise clients. We’re hiring a Principle AI Data Scientist to design LLM solutions, defend the choices behind them, and turn deep model knowledge into results clients will pay for.

This is not a back office research role. You’ll work directly with client engineering leads and senior technical stakeholders, from the first whiteboard session to production deployment.

Why this role stands out

  • Real architect-level ownership. You’ll shape how LLMs are fine-tuned, evaluated and deployed for named enterprise accounts. You won’t be working through someone else’s backlog.
  • A ground-floor opportunity. You’ll help build a new AI practice inside an established, commercially stable business, rather than competing for attention at a crowded AI startup.
  • Science that stays sharp. You’ll join a small, technically elite team where “customer-facing” doesn’t mean watering down the science. It means being trusted to represent it.
  • Visible impact. The people making buying and build decisions will see and value your technical depth.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

What you’ll be doing

  • Acting as the main technical point of contact for enterprise clients on LLM projects, from scoping through to deployment
  • Designing LLM training, fine-tuning and evaluation pipelines for each client’s use case and data environment
  • Turning unclear client requirements into concrete technical architectures and delivery plans
  • Leading technical discovery and whiteboard sessions with client engineering and data science teams
  • Owning model performance, evaluation methodology and responsible deployment recommendations
  • Working with sales, account management and delivery to make sure every design is technically sound and can be delivered commercially within a managed services model

What you’ll bring

  • 5+ years in applied data science or ML engineering, with hands-on LLM training or fine-tuning experience beyond API use
  • Practical experience with transformer architectures, LLM pre-training or fine-tuning workflows, and modern ML frameworks such as PyTorch or Hugging Face
  • A strong grounding in evaluation methodology, the trade-offs between RAG and fine-tuning, and production ML deployment patterns
  • Confidence and credibility with senior technical stakeholders. You’re comfortable with pushback in live technical discussions and equally at home in a boardroom or a terminal.

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Nice to have

  • Experience with distributed training infrastructure (multi-GPU, multi-node)
  • A background in pre-sales, solutions architecture or consulting
  • Familiarity with model safety, alignment or responsible AI evaluation frameworks
  • Experience in an MSP, systems integrator or managed services environment

Interested?

If you want your technical depth to be seen, trusted and valued by the people making the decisions, we’d love to hear from you.

Location: London

Salary: £100,000 - £120,000 Depending On Experience

Working pattern: Hybrid

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Location

London, England, United Kingdom

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