Lead Data Scientist

Belfast
1 week ago
Create job alert

Are you an experienced Lead Data Scientist looking to shape AI strategy, mentor a high‑performing team, and work on cutting‑edge LLM and generative AI projects? Our client, a growing data & AI consultancy, is hiring a technical leader to drive innovation and deliver high‑impact solutions for customers across multiple industries.
This role includes leading a team of four and acting as deputy for the Engineering Manager when required.
⭐ Why This Role Stands Out

Work with advanced machine learning, generative AI, LLMs, and modern analytics technologies.
Lead and develop a talented data science team.
Blend hands‑on technical delivery with strategic influence.
Hybrid working, excellent benefits, and strong investment in your professional growth.Key Responsibilities

Lead and mentor a team of 4 data scientists, supporting skills' development, career growth and project delivery.
Deliver end‑to‑end data science and AI solutions across multiple client projects.
Build and deploy machine learning models, including LLM‑powered and generative AI applications.
Run client workshops, gather requirements and translate business challenges into data‑driven solutions.
Review code, set best practices and drive high standards in model development and engineering.
Contribute to technical roadmaps and product innovation.
Act as stand‑in for the Engineering Manager, supporting delivery governance and technical leadership. Skills & Experience Needed

Strong commercial experience in data science, machine learning and AI.
Hands‑on experience with LLMs, generative AI, NLP, or advanced modelling techniques.
Proficiency in Python, SQL and modern data science libraries (e.g., PyTorch, TensorFlow, scikit‑learn, HuggingFace).
Experience mentoring or managing data scientists.
Confident working in Agile environments with Git/version control.
Strong communication skills, especially with non‑technical customers. Desirable (SEO‑Optimised)

Experience with cloud platforms (AWS, Azure, GCP).
Docker/Kubernetes & modern MLOps tooling.
Experience across NLP, tabular modelling or computer vision.
Exposure to LangChain, vector databases or AI‑augmented development workflows. Benefits

35 days leave, including public holidays.
Optional additional unpaid leave.
Hybrid and flexible working.
Pension + private health insurance.
Funding for training, learning resources and conferences.
Regular knowledge‑sharing sessions and team events. How to ApplySubmit your CV through Hays or contact your Hays consultant for more details.

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

Related Jobs

View all jobs

Lead Data & AI Scientist

Lead Data Engineer

Data Scientist - Optimisation

Manufacturing Data Scientist

Manufacturing Data Scientist

Lead Software Engineer

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 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 .

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

Cloud computing underpins almost every modern digital service. From financial systems and healthcare platforms to AI, e-commerce, government infrastructure and cybersecurity, the cloud is now the default operating environment for UK organisations. Demand for cloud professionals has grown rapidly, with roles spanning architecture, engineering, security, DevOps, platform operations and cost optimisation. Salaries remain high, and vacancies remain stubbornly difficult to fill. Yet despite a growing number of graduates with computer science, IT and software engineering degrees, employers across the UK report a persistent problem: Too many candidates are not job-ready for real cloud computing roles. This is not a question of intelligence or motivation. It is a structural skills gap between what universities teach and what cloud jobs actually require. This article explores that gap in depth: what universities do well, what they consistently miss, why the gap exists, what employers genuinely want, and how jobseekers can bridge the divide to build sustainable careers in cloud computing.