Lead Data Scientist

SPG Resourcing
Manchester
1 week ago
Create job alert

Lead Data Scientist

Location: South Manchester – Hybrid (after 3 months)

Salary: £65,000-£80,000 (Negotiable)

Type: Permanent


We are hiring a Lead Data Scientist to join a growing, customer facing data science practice within an established digital transformation consultancy.


You will deliver impactful tech for good programmes across Civil Defence, Healthcare, Sustainable Environment and Digital Democracy, working directly with customers to solve complex, high value problems.


The Role:

  • Build effective working relationships with key customer & third party stakeholders, leading interactions within your domain
  • Work with customers to scope technical requirements and solution design
  • Own the end to end design and implementation of larger scale data science solutions, assuring development and maintenance of strong documentation, and ensuring that designs are translated into implementation
  • Own the full lifecycle from design and build through to deployment and continuous improvement across larger data science services
  • Work in agile, multidisciplinary teams alongside Engineers and UCD specialists
  • Act as point of technical assurance for the work of junior practitioners, and support Senior practitioners to maximise quality and pace
  • Support with recruitment and training activities to enable continued growth of the data science capability


You will be acting as one of the main faces of the business on larger scale Data Science services, responsible for technical design, customer stakeholder management, assurance & deployment.


What we are looking for:

  • Strong commercial data science experience in Agile environments
  • Excellent stakeholder management skills, ability to quickly build credibility and rapport with both technical and non-technical stakeholders
  • Good Python or R skills, writing production ready code
  • Experience with AWS, Azure or GCP
  • Experience deploying models into live environments
  • Experience working with sensitive data and understanding governance best practice
  • Ability to clearly communicate complex technical outputs to stakeholders
  • Ability to accurately translate client requirements into technical solutions, and


Desirable:

  • NLP experience
  • Experience deploying Generative AI applications, such as chatbots or RAG systems
  • Consultancy or professional services background would be advantageous


If you are a Lead Data Scientist who enjoys customer interaction and are looking to advance your career whilst helping deliver some of the UK’s most important tech for good projects, we’d love to hear from you.

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

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.

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.

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.

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.