Lead Data Scientist / Tech Scale Up / £120,000

Opus Recruitment Solutions
London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Senior Data Scientist

Data Scientist II - QuantumBlack Labs

Lead Data Scientist – High‑Impact Role (Exclusive Search)


I’m working with a rapidly scaling European tech organisation that’s delivering major cloud, data and digital programmes for household‑name enterprise clients. They’re now looking for a Lead Data Scientist to take the reins on a flagship London engagement - and the scope here is huge.

If you’re someone who loves stepping into a role where you can set direction, elevate standards, and actually shape how data gets used across a business, this one’s going to grab you.


Why this role stands out

  • You’ll be the senior voice for Data Science on a major transformation programme.
  • You’ll lead a talented, multi‑location team and define how they deliver.
  • You’ll work directly with senior decision‑makers - your ideas won’t sit on a shelf.
  • The work is varied, complex, and genuinely business‑critical.
  • The company is growing fast, creating real headroom for your own progression.


Hybrid setup: 3 days a week in London with the client.


What they want to see

  • Strong experience shipping data‑driven or analytical solutions into production.
  • Confident leadership of Data Science teams - setting standards, reviewing work, driving quality.
  • Someone who can turn complexity into clarity and win trust with senior stakeholders.
  • A solid understanding of modelling approaches and how to deliver them properly.
  • Experience working in structured, quality‑driven environments.


What you’ll be leading

  • Full‑cycle delivery of high‑value data solutions used across the business.
  • Establishing delivery frameworks, governance, and best practice for the discipline.
  • Partnering with senior leaders to define priorities and shape delivery strategy.
  • Developing Data Scientists and levelling up the team's capability.
  • Ensuring consistency of approach across international teams.


Nice extras (not essential)

  • Postgrad in a relevant field
  • Consulting / professional services background
  • Experience in regulated or operationally complex environments
  • Interest in responsible, well‑governed use of data


Why it’s worth a conversation

  • Seriously impressive growth trajectory
  • Big‑picture influence without losing hands‑on depth
  • Strong L&D culture and clear progression routes
  • Competitive salary + flexibility + a genuinely supportive environment

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.