Lead Data Scientist - ML & AI Projects

Datatech Analytics
Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist (Defence) - Onsite UK Clients

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

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

Lead Data Scientist – ML & AI projects

Competitive annual salary of up to £90,000 dependent on experience

Hybrid working – Bristol office base (currently 2 days in office but expected to move to 3)

Ref J12883


Unfortunately, no sponsorship available with this client so full UK working rights required


Our client is seeking to recruit a new Lead Data Scientist to lead data science initiatives and drive innovation in the healthcare industry. You’ll have the opportunity to leverage your expertise in data analysis and machine learning within our dynamic and forward-thinking team, to shape the future of healthcare. If you’re passionate about making a real impact and are ready to lead a team of talented data scientists, we want to hear from you.

What you’ll be doing:

Lead a relatively small team of data scientists in developing and implementing advanced data analytics, machine learning and traditional and generative AI solutions, to address complex challenges in healthcare.

Collaborate with cross-functional teams to identify business opportunities, define data science strategies, and drive the development of innovative products and services.

Oversee the end-to-end process of data collection, pre-processing, analysis, and model development to derive actionable insights and improve decision-making.

Drive the development and deployment of scalable and efficient machine learning models and algorithms to enhance healthcare services and optimize business operations.

Mentor and coach junior data scientists, fostering a culture of continuous learning, innovation, and excellence in data science practices.

What you’ll bring:

In depth experience coaching and leading junior data scientists within a senior data science role.

Demonstrable experience of developing complex AI projects with minimal supervision, working in line with best practices.

Working knowledge of extracting business value from data science methods using both quantitative and qualitative metrics.

Strong mathematical and statistical background.

Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark.

Experience and understanding of mixed technical teams such as engineering, architects, business analysts.

Familiar with MLOps industry best practices.

Good stakeholder communication skills with proven ability to translate complex scientific findings to non-technical stakeholders.

Understanding of the financial industry, in particular insurance, would be advantageous.


If this sounds like you, please make an application and we’ll be in touch.

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.

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.