Lead Data & AI Scientist

London
2 weeks ago
Create job alert

Lead Data & AI Scientist
Hybrid: 1-2 days per week in the office (London)
Permanent
£100k-£150k DOE + Bonus + Benefits

Experis are delighted to be partnering with a leading and well-respected organisation as they continue to invest heavily in Data Science, Artificial Intelligence and Generative AI. We are supporting them in the search for an experienced Lead Data Scientist to shape, scale and lead their enterprise-wide AI capability.

This is a high-impact, strategic role with responsibility for defining the direction of Data Science and AI across the organisation. You will lead the delivery of production-grade ML and GenAI solutions, build a high-performing specialist team, and partner closely with senior stakeholders to drive measurable business value.

What You'll Be Doing

Leading the design, development and productionisation of Machine Learning, AI and GenAI solutions across the business.
Defining technical standards, best practices and governance for Data Science and MLOps.
Identifying and prioritising high-impact use cases in partnership with Wealth, Enablement and Technology teams.
Building, mentoring and developing a high-performing Data Science team.
Embedding modern MLOps practices including CI/CD, model monitoring, feature stores and version control.
Working closely with Data Engineering, Architecture and Operations teams to ensure scalable, secure deployment.
Acting as a senior technical authority and thought leader in advanced analytics and AI.
Championing innovation, experimentation and continuous improvement in AI and analytics delivery.

Experience Required

Proven experience in Head of or lead-level Data Science, AI or Machine Learning roles within enterprise environments.
Strong Python and SQL skills, with experience developing production-grade analytical solutions.
Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake).
Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow).
Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases).
Strong knowledge of MLOps tooling and practices (MLflow, CI/CD, containerisation, monitoring).
Experience leading, mentoring and developing technical teams.

If you'd like to learn more, please contact Jacob Ferdinand at

Related Jobs

View all jobs

Lead Data & AI Scientist

Lead Data Scientist

Developer (AI/RPA) (18 Months FTC)

Lead Software Engineer

Forward Deployed Engineer

Cyber Security Lead

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.

Cloud Engineer Jobs in the UK: Salary, Skills, Career Paths & How to Get Hired

Cloud engineer jobs are among the fastest-growing technology roles in the UK. As organisations move infrastructure, applications and data into the cloud, demand for skilled cloud professionals continues to surge across finance, healthcare, retail, defence, government and high-growth startups. If you’re exploring a career in cloud engineering — or looking for your next role — this guide covers everything you need to know: What a cloud engineer does Types of cloud engineer jobs Required skills and certifications UK salary expectations Career progression pathways How to land a cloud engineer job in the UK Whether you’re a graduate, IT professional transitioning into cloud, or an experienced engineer looking to specialise, this article will help you position yourself competitively.

How Many Cloud Computing Tools Do You Need to Know to Get a Cloud Job?

If you are aiming for a role in cloud computing, it can feel like the skills list never ends. One job advert asks for AWS, Terraform and Kubernetes. Another mentions Azure DevOps, PowerShell and ARM templates. A third throws in Docker, Python, Linux, CI/CD, monitoring tools and security frameworks. It is no surprise that many cloud job seekers feel overwhelmed before they even apply. Here is the reality most cloud hiring managers agree on: they are not hiring you because you know every cloud tool. They are hiring you because you understand cloud concepts, can design reliable systems, manage costs, keep things secure and support real workloads. Tools matter, but only when they support outcomes. So how many cloud computing tools do you actually need to know to get a job? For most roles, the answer is far fewer than you think. This article explains what employers really expect, which tools are essential, which are role-specific, and how to focus your learning so you look capable and employable rather than scattered.

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

anding a job in cloud computing can be highly competitive — especially in the UK market where demand far outpaces supply in many segments. Whether you’re aiming for roles in Cloud Engineering, DevOps, Site Reliability, Cloud Architecture, Security, Data/Analytics, or Platform Operations, hiring managers screen applications quickly and with specific priorities in mind. Hiring managers don’t read every detail at first; they scan for critical signals in the first 10–20 seconds. These early signals determine whether your CV gets read more closely, whether your LinkedIn profile gets clicked, and whether you’re invited to interview. This guide breaks down, in practical terms, exactly what hiring managers look for first in cloud computing applications — and what you should emphasise in your CV, cover letter and portfolio to stand out on www.cloudcomputingjobs.co.uk .