Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Scientist – Bristol

Kendleshire
11 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist: AI/ML, MLOps & Cloud

Senior Data Scientist

Data Science Engineering Manager - Audit

Data Science Engineering Manager - Audit

Data Science Engineering Manager - Audit

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.